Complexity Economics, Applied Spirituality and Public Policy (CEASP)
- The primary aim of the Centre is to build networks among interested faculty and students, nationally and internationally, and develop a community of practice among policymakers and practitioners.
- The Centre will consider providing opportunities for research scholars to meet and engage, and to resolve public policy challenges through the lenses of complexity economics and applied spirituality.
- The approach will be transdisciplinary drawing from related fields of complexity theory, behavioral economics, psychology, post-growth economics, econophysics and sociophysics, quantum decision theory, artificial intelligence, sustainability science, law, etc.
Prof. (Dr.) Naresh Singh
Vice Dean & Professor, Centre for Complexity Economics and Applied Spirituality for Public Policy
He teaches courses on Complexity and Public Policy, Legal Empowerment of the Poor, Systems Thinking as a Strategy for Sustainable Development Policy and Applied Spirituality and Public Policy. He has published several books and journal articles.
Prof. Singh has a wide range of research interests in the areas in which he teaches and public policy design and evaluation. His work focuses upon decision-making in complex situations, including conflict and peacebuilding, sustainable livelihoods, transformations for catalyzing SDG achievement, international development cooperation, technology policy, complexity theory, and the politics of being. Professor Singh taught at many universities, including Boston, Harvard, Fordham McGill, Waterloo and Guelph. He is presently a visiting professor at the University of Ottawa.
He has been a consultant/adviser to the United Nations Development Program, the Commonwealth Secretariat, the Pan American Health Organization, the International Labour Organization and the Food and Agriculture Organization.
Prof. Sudarshan Ramaswamy
Dean and Professor, Executive Director, Centre for Global Governance and Policy
In 1984 he served in the Ford Foundation’s South Asia Office in New Delhi as Assistant Representative and Program Officer for Human Rights and Social Justice. In 1991 he joined the UNDP in India as Senior Economist and Assistant Representative for Governance and Public Policy. In 2000 he served UNDP in Jakarta as its Senior Governance Advisor. In 2002 he was appointed Policy Advisor for Justice and Governance in the UNDP Oslo Governance Centre. In 2005, he was transferred to the UNDP Asia-Pacific Centre in Bangkok, where he was Regional Policy Advisor for Governance, Human Rights, Rule of Law, Justice, and Legal Reforms.
In 2012 he joined the O.P. Jindal Global (Institution of Eminence Deemed To Be University) as the founding Dean of the Jindal School of Government and Public Policy. He has an impressive track record of publications comprising books, articles, and UN policy reports, reflecting his inter-disciplinary research, teaching and policy experience in development programmes, human development, law, governance, institutions and policy.
Prof. Anirban Chakraborti
Founding Member, CEASP
Dr. Debajit Jha
Deputy Executive Director, CEASP
Dr. Jha is associated with a group of people working in the field of Econophysics for a long period. He is a macroeconomists by training and works in the area of Macro-development Economics. His primary research interest is empirical growth economics – convergence club, polarization, structural change, dynamics of regional income, growth and distribution episodes, role of institutions on development, and labour migration.
Dr Sudip Patra
Deputy Executive Director, CEASP
Dr Sudip Patra is founding member and currently executive deputy director of CEASP. Sudip is an associate professor at OP Jindal Global University, JSGP.
Sudip obtained his PhD in mathematical modelling in finance from University of Glasgow, Scotland with a prior Physics education. Sudip’s works are in inter-disciplinary areas: quantum-like modelling, quantum foundations, and philosophy of science in general. Sudip is offering courses at masters and possibly PhD level in complexity economics. Sudip has been collaborating with pioneering scientists, for example Stuart Kauffman and Menas Kafatos in US, and Partha Ghose in India.
His research profile can be found at https://www.researchgate.net/profile/Sudip-Patra
Dr. Shivangi Chandel
Assistant Professor, JSGP
Dr. Shivangi Chandel is an Assistant Professor in Jindal School of Government and Public Policy (JSGP) of O.P. Jindal Global (Institution of Eminence Deemed To Be University) since 2019. She completed her doctorate in Economics from Indira Gandhi Institute of Development Research. She received a master’s degree in Mathematics from the Indian Institute of Technology Kanpur, and a bachelor’s degree with honours in Mathematics from Hindu College, University of Delhi. Prior to joining JSGP, she taught several courses in mathematics, microeconomics, and game theory in undergraduate and post-graduate programmes at the Department of Economics, Jamia Millia Islamia, New Delhi, and the Department of Civics and Politics, University of Mumbai.
Her research interests lie in Microeconomic Theory and Mechanism Design with a focus on Auctions. In her doctoral thesis, she examines corruption in the form of quality manipulation in procurement auctions where the auctioneer could accept a lower quality product in exchange for a bribe. She is particularly interested in procurement auction designs that emerge due to secondary policy objectives like promoting growth in domestic industry, sustainable green growth etc. Recently, she has extended her research interests into applications of quantum-like cognition modelling in game theory (https://www.researchgate.net/profile/Shivangi-Chandel).
She offers both compulsory and elective courses on Game Theory and Mathematics at the school. She serves as Assistant Dean for JSGP Conferences and Open Lectures and is a member of the Centre of Complexity Economics, Applied Spirituality, and Public Policy (CEASP).
Ms. Divya Bhatnagar
Lecturer and Researcher, Research, CEASP>
She has completed her Master of Public Policy at the University of Chicago and earned a certificate in International Development and another certificate in Global Conflict Studies. She has worked at UNICEF (UN headquarters, New York) in Division of Data, Research, and Policy in the Education Section and the Child Poverty Section. She later worked in the Office of Innovation at UNICEF (UN headquarters, New York) researching education technology to reach children in low-resource and low-connectivity areas. Most recently, she worked at Giri Institute of Development Studies working on analyzing the Indian government’s project of Samagra Shiksha Abhiyan and the UNDP program on community health. Divya has a background in Electrical Engineering and she has previously worked in the field of Astrophysics. She worked on the project for the elimination of uncertainty in measurements of dark energy at the University of Victoria, Canada. Divya is interested in International Development.
Her research interests include sustainable development policy, children, education, gender, spirituality, and peace & law. Her other research interests include physics, psychology, and philosophy.
Academic Tutor and TRIP Fellow
Dr. Namesh Killemsetty
Assistant Professor, JSGP and Member, CEASP
Dr. Namesh Killemsetty is an Assistant Professor in the Jindal School of Government and Policy, O.P. Jindal Global University. He completed his Ph.D. in Public Policy from the University of Massachusetts Boston in 2021. He also has an M.S. in Public Policy from the University of Massachusetts Boston, M.Tech in Infrastructure Management from CEPT University Ahmedabad and B.Tech in Civil Engineering from MNNIT Allahabad.
As a transdisciplinary researcher working in urban governance and poverty, Namesh’s work particularly focuses on housing, tenure security, and community rights of slum dwellers integrating theories and methods from Urban Studies, Policy Analysis, Operations Research, and Decision Sciences. Namesh is the recipient of the 2021 Urban Affairs Association Alma H. Young Emerging Scholar Award, USA. He has been previously awarded as one of the global winners in a Research competition on Urban Development by Woodrow Wilson International Center for Scholars, USAID, and the World Bank Group. Namesh teaches courses on Urban Poverty, Statistics, and State & Governance.
Assistant Professor of Law and Assistant Dean for LL.M, JGLS
Prajakta Kale is currently Assistant Professor of Law and Assistant Dean for LL.M. Blended Programme at Jindal Global Law School (JGLS), India. She holds LLM from Queen Mary University of London, with specialisation in Computer/Cyber Law, IPR and International Banking. She pursued her undergraduate studies in Law and Engineering. She completed LL.B. and B.E. in Information Technology from Dr. Babasaheb Ambedkar Marathwada University, Aurangabad and has consistently excelled in academics holding top University ranks.
At JGLS she has been engaged in teaching courses on IPR, Professional Ethics and Bar-Bench Relationships, Constitutional Law, and Law of Crimes. Her area of interest is at intersection of law, technology and society. She has keen interest in research on Machine Ethics and is curious about studying legal aspects of technologies like Artificial Intelligence, Machine Learning, Blockchain, and other legal issues concerning technology viz. Data Protection, IP, Cyber Crime, Cyber Security. She is engaged in research activities of Centre for Complexity Economics, Applied Spirituality and Public Policy (CEASP) at the Jindal School of Government and Public Policy.
Prior to joining JGLS, she has worked for qLegal, the Legal Advice Center of Queen Mary University of London, which provides free legal advice to tech start-up companies and Entrepreneurs. As part of this assignment, she externed with Belgium based techno legal start-up ‘Lawren’, where she worked on AI based legal chat bot for UK market. She is recipient of 2018/19 Prieskel Essay Prize for best legal essay on Computer and Communication law subject as judged by Prieskel & Co LLP, London.
She had been actively involved in extracurricular activities. She was selected as ‘Student Leader’ in 1st Indian Students Parliament at Pune where she presented her views on ‘Women Empowerment’ and got an opportunity to visit significant organizations viz. International Court of Justice and International Criminal Court at The Hague, Netherlands, UNESCO HQ at Paris, WTO HQ at Geneva, Commonwealth Secretariat at London, The European Parliament and NATO HQ at Brussels, Belgium. This International exposure in the early stage of career influenced her thought process and triggered her to make a shift from purely technical domain to that of humanities and social sciences.
She is practitioner of Sahaj yoga meditation since past 20 years and has conducted stress management and meditation workshops in several education institutions.
Dr K. Parameswaran
Associate Professor of Law and Former Dean of Academics at Gujarat National Law University (GNLU), India
Dr. K. Parameswaran is an Associate Professor of Law and Former Dean of Academics at Gujarat National Law University, GNLU, India. He also taught at NLSIU Bangalore, NLU, Jodhpur, Madras University, SLS, Pune etc. He is also part of various academic and research bodies dealing with higher education & research.
He pioneered a law subject titled “Law, Religion, Spirituality & Justice”, and also a method of Ethics Skills Development (ESD) for professional integrity and excellence.
He is highly proficient and certified in Cognitive Behavioural Psychotherapy (CBT), Integrated Clinical Hypnotherapy & a Master-Trainer of Neuro Linguistic Programing (NLP).
He was formerly a Governing Board Member of Auroville Foundation, Govt of India., and UNESCO, associated with World Commission on Environmental Law, International Consortium for Law and Religion, Project for Integrating Spirituality, Law and Politics, Inter-faith Dialogue and Conflict-mitigation, Vedic Studies and Indian Heritage etc.
His core work is to bring spiritual awareness & peace values in legal research for future humanity, writes on contemporary issues keeping Sri Aurobindo’s integral knowledge for individual & collective developments, higher harmony & deeper well-being.
He extensively lectures in India and abroad, and takes specific interest to bring skills and capacity-building to students, advocates, judicial officers, Ph.D., scholars etc., through immersive workshops & FDPs. He is confident that the integration of knowledge & necessary competencies from different disciplines can usher our new humanity and society a promising future.
- Complexity Economics
- Applied Spirituality
- QLM, QSS
EC-46: Complexity Approaches to Public Policy
SPAS-7213: Sustainable Development Policy and Applied Spirituality
TSYS-7206: Thinking in Systems: A strategy for Sustainable Development Policy
Adaptive and Anticipatory Governance
- Spring, 2021 EC-46: Complexity Approaches to Public Policy
- Fall, 2021 TSYS-7206: Thinking in Systems: A strategy for Sustainable Development Policy
- Spring, 2022 Sustainable Development Policy and Applied Spirituality
- Spring, 2022 Complexity Economics
- Book Chapter: Ch-17: Development as Emergent Creativity
- Article in magazine the Ordinary Mercantile: Complexity and Public Policy, by Prof. Singh
- Journal Paper: Phase separation and scaling in correlation structures of financial markets, Prof. Chakraborty et al.
- Journal Paper: Network-centric Indicators for Fragility in Global Financial Indices, Prof. Chakraborty et al.
- Journal Paper: Distress propagation on production networks: Coarse-graining and modularity of linkages, Prof. Chakraborty et al.
- Journal Paper: Network geometry and market instability, Prof. Chakraborty
- Quantum -like modelling in game theory, Prof. Patra
- Sudip Patra, Measurement, Lüders and von Neumann projections and non-locality | SpringerLinkhttps://link.springer.com/article/10.1007/s12043-021-02278-8
- Time series analysis of rainfall for the state of Odisha, AIP Conference Proceedings 2435, 020051 (2022); https://doi.org/10.1063/5.0083522
Rajni and Sudip Patra
- Quantum-like Modelling Paradigm: Modelling Pandemic, Dr. Sudip Patra
Complexity Economic Book Project
This book examines the economy as a complex adaptive system and deduces the implications for public policy assessing alternatives to market and policy failures which result from current mainstream economic thinking. It is intended as an introductory text for students and faculty in the fields of both economics and public policy. The interdisciplinary perspective put forward in this book by collective efforts of economists, physicists, environmental scientists, mathematicians, system thinkers, and complex systems researchers not just contributes to bringing their diverse knowledge to the theoretical and methodological aspects, but also bridge the pedagogical and ideological gap that exists between conception, reading and learning such curriculum. It covers the history of complexity economics, the central basic concepts and methodological tools, application and case studies of complexity thinking in economics and public policy, introduction to novel paradigms of quantum-like modeling and quantum games as well as extensions that go far beyond the traditional thinking. Furthermore, the coverage of a wide range of aspects of complexity thinking and their linkages to economics and public policies via enriching examples makes it a valuable resource for academicians, researchers, students, and practitioners in the relevant studies.
Sustainable Development Policy and Applied Spirituality Book Project
This book aims to bring about a new development model that is not just based on narrow definitions of GDP and economic growth, rather a model that includes the overall development of the social, environmental, and inner dimensions of all individuals and the planet. This book is expected to have a readership among post-graduate students, faculty, policymakers, and politicians searching for methods and frameworks for sustainable development. In addition, it is likely that there will be a significant readership among engaged lay readers. The objective is to put forth an interdisciplinary perspective and address topics in spirituality, consciousness studies, public policy, law, gender, Indic and Buddhist philosophy, Gandhian thinking, and inter-link quantum physics with consciousness models. The book brings the cross-cutting knowledge from the expertise of professionals from fields of Public Policy, Economics, Law, Philosophy, Gender Studies, Environmental Science, and Physics. The goal is to rejuvenate how we think about development, nurture appreciation and development of our true nature, and bring about changes at the policy level for all-inclusive growth and sustainable development.
- Quantum Foundations and Decision Theory with Prof Partha Ghose
- Consciousness – Quantum Link with Prof Menas Kafatos
- Human Learning Systems with CPI, India
HLS or Human learning systems is an approach to public service management that recognizes the person’s freedom to determine what it means to flourish in one’s life. The term ‘Human’ in HLS signals towards the moral purpose of public service being the enablement of human freedom and human flourishing. It thus answers the ‘why’ aspect of public service management. The term ‘learning’ associates itself with answering the ‘how’ aspect of public service management i.e., the strategies that need to be employed for achieving the moral purpose. The focus of HLS is on understanding the people inter subjectively i.e., seeing them in the context of their complex web of relationships that define who they are. The public service in HLS is therefore tailored to meet the needs of every person from the perspective of their specific life context. The term ‘system’ in HLS is the units to which the purpose and outlined strategy are applied. Systems determine the desirability of the outcome.
The project, in collaboration with the Centre for Public Impact (CPI), India aims to:
- To develop a good understanding of how Public service is delivered and managed in India
- To understand whether HLS can make a difference in the delivery of Public service in India and if so, how?
- Discover & learn about the possible approaches that have worked in Indian scenarios and the ones that have failed
Sharing Global Perspectives with Centre for New Economic Studies (CNES)
This project under the umbrella title “A program exploring what can be learnt from lived experiences since 2020” is led by a group of driven individuals from research groups in Aberdeen, Stanford, and Wisconsin Universities, in collaboration with the Cynefin Centre, with the purpose to generate an open access platform that can bring individual voices and experiences around the world to light and believing that building these narratives can provide insights, understanding and compassion to the global community.
This project in particular will allow CEASP and CNES to understand the unexplored narratives and experiences during the pandemic. In what has been a unique collective experience across the globe, the project will be able to capture the similarities and differences between countries thereby bringing to light culturally and experientially unique aspects of Covid-19.
As we aim for this collaborative work, through this program, we are bringing together the work at CNES of linking economic theory with historical experience(s) and empirical observation, and the work at CEASP of striving for vibrant research on the forefront of Complexity Theory on a common shared platform.
SEEDS, a DeFi protocol, aims at delivering a conscious currency with direct democracy for a regenerative economy. It is imperative to note that SEEDS is focusing on an ecosystem which will promote decentralized monetary policies and a decentralized governance system (through DAO’s). It aims at replacing the current centralized governance structure and empowering an obvious alternative to the corporate backed cryptocurrencies.
This project is in collaboration with Dr. Anneloes Smitsman, Futurist, evolutionary systems scientist, system architect, and global catalyst for thriving civilizations
- Centre for public impact CPI (CPI India) – Human Learning Systems
- Sharing Global Perspectives and CNES
- IJPP Call for Papers: https://www.inderscience.com/info/ingeneral/cfp.php?id=5553
- Book Launch: Transforming: Applying Spirituality, Emergent Creativity and Reconciliation. Lexington Books, 2021 – https://www.youtube.com/watch?v=DCH-MFwpPYs
- Talks – Michael’s webinar https://www.youtube.com/watch?v=Z4_005lGn3E&t=1s
- Guest Lectures – Understanding Advaita Vedanta and Swami Vivekananda’s Ontological Ethics.
- IPPA Panel of Innovative Approaches to Public Policy, July 2021 – https://www.ippapublicpolicy.org/conference/icpp5-barcelona-2021/panel-list/13/panel/innovative-approaches-to-addressing-contemporary-wicked-problems-in-public-policy/1137
- CEASP proudly announced to be a co-convening partner in World Unity Week, June 2021 – https://www.facebook.com/watch/live/?v=348947016594824&ref=watch_permalink
- Designing and Constitutionalizing the New Paradigm in Politics. CEASP with Laszlo Institute. – https://www.youtube.com/watch?v=5POxTSDmhZo
- Session on Quantum-like modelling, ACEP – https://www.youtube.com/watch?v=dn1T2haylNE
- Session on Complexity Economics, ACEP – https://www.youtube.com/watch?v=NbmwZX5PJ38&t=5450s
- Book Launch: Politics of Being by Dr. Thomas Legrand (YouTube Link – https://www.youtube.com/watch?v=9XfroKwBNls&t=1577s)
- Guest Lecture by Dr. Menas Kafatos on Spirituality and Science – https://www.youtube.com/watch?v=Et2Vk9WLWmM
- Guest Lecture by Dr. Donald Hoffman on The Case Against Reality –https://www.youtube.com/watch?v=rjNLmnpq4Zw
- Book Launch – April 9th, 2022 – Buddhist and Daoist Systems by Prof. Josep Coll
Fall, 2022 – Adaptive and Anticipatory Governance
Virtual Open Lecture – April 19th, 2022 – Human Evolution and the Challenges of the Anthropocene: How can complexity sciences help? By Stuart Kauffman
Reading and Discussion Circles 2.0 (2021-2022)
Quantum Social Sciences and Public Policy
Introduction to QSS for public policy
Prof. Sudip Patra
February 2nd, 2021
Introduction to computational models
Prof. Anirban Chakraborty
February 15th, 2021
and Public Policy
Introduction to Applied Spirituality for Public Policy
Prof. Naresh Singh
March 1st, 2021
Sustainability through the Complexity Lens
Focused on how sustainable development can be seen through and linked to the complex adaptive system by building on the framework of sustainability science
Ms. Cheshta Grover, TRIP Fellow
April 5th, 2021
Complexity and Public Policy In Singapore
Focused on recognizing wicked problems in Singapore and approaching towards a solution from Complexity Thinking
Prof. Siew Ann Cheong, NTU, Singapore
May 3rd, 2021
Introduction to R&DCs
Prof. Naresh Singh
Oct 20th, 2021
Complexity and Public Policy
Ms. Sumalatha KC
Nov 20th, 2021
Applied Spirituality and Public Policy
Ms. Poorva Israni
Feb 12th, 2022
Complexity and Sustainability
Ms. Pritika Jain
Feb 26th, 2022
What is Quantum Social Science approach?
And what we aspire in CEASP to achieve?
Dr. Sudip Patra
The Jindal School of Government and Public Policy has set up a truly interdisciplinary center, Center for Complexity Economics, Applied spirituality and Public policy or CEASP. The center will explore some novel emerging paradigms, which can be extended to resolve pressing public policy issues, including social dynamical, economical and financial system problems, Quantum like modelling in social science or quantum social science (QSS) is one of the emerging paradigms. In this brief introduction we will just touch upon the basic framework of QSS, and also try to clarify any confusions relating to the same. References to relevant seminal works are provided in the end for interested readers.
QSS is purely a novel exercise of extending and constructing suitable formalisms (mathematical and conceptual) based on widely practiced formalisms in physical sciences, mainly quantum mechanics and quantum field theory, to analyzing human decision making or social dynamics at large. Several advantages of this approach, have been demonstrated over the last few decades (references in the end), over standard neoclassical decision theory, or even standard behavioral economics or finance theories. We will attempt to discuss some of the advances in brief here. However, from the onset we need to be very clear that we are in no way suggesting any underlying physics of social systems. Social systems (political, economic, financial etc) are at a very high emergent level as compared to say particle physics level, and the beauty of emergent systems is that we need not bother tracking in full details the absolute microstates. Coarse graining is perfectly applicable. It is a significant shift from reductionism to holism.
However, various limitations in formal logical or mathematical models, for example in Boolean logic-based decision theory, Constrained Utility Maximization theory, or General Equilibrium theory in macroeconomics, have shown that there is a strong need to come up with more apt and coherent formalisms to describe real life behavior of decision makers. Quantum mathematical and logical formalisms have provided better resolutions. Certainly, the standard behavioral school, or schools of modelling too have responded to such limitations, but we claim that QSS is more suitable to provide coherent frameworks rather than more dispersed heuristics-based approaches.
Decision theory approach
Since the 1960s many cognitive scientists have noted in detail (for example Ellsberg Paradox, Linda Paradox, Prospect theory which are wonderfully summarized in the book ‘thinking fast and slow’) that typical Boolean Logic based decision-making models don’t explain many features of human decision making. Particularly decision making in a context of uncertainty .. In neoclassical economics, uncertainty has been mainly described with the help of classical probability theory, or modified by Bayesian updating rules, which then is supplemented with expected utility maximization models. But what about such scenarios where ambiguity is deep, and it is difficult to form ‘rational’ beliefs? In real life we face such scenarios often. Again, there are rare events like ongoing pandemic or financial crises, what might be better ways to deal with such phenomena in terms of decision making? Cognitive experiments for decades (well summarized in the book ‘quantum social science’) have shown people behave differently under such contexts compared to predictions of standard decision theories.
Real prisoner’s dilemma games are an example, where players don’t choose the typical dominant ‘defection’ equilibrium, when they are not at all in a context of forming beliefs about other players moves. Hence, scientists since late 90s (for example see the book ‘Ubiquitous Quantum Structure’) have suggested there might be a possibility for constructing a more general probability framework, which might contain the standard results but also help in describing so called deviations, or anomalies. It turned out that ‘quantum probability’ framework, which is a mathematical formalism based on description of states of a system in Hilbert space, and computing probabilities in such a space of events using ‘Born’s rule’, could be such a comprehensive set up. Now there are stark differences between such a formalism and classical set theory-based decision modelling, but ONLY in the mathematical set up.. We will urge readers to look into the book ‘quantum social science’ for details.
It turned out from experimental data that rules used for computing probabilities in such a format provided results which described deviations from standard theories to a great extent. So much so that a new sub set of studies, called quantum decision theory, blossomed (refs in the end).
Quantum decision theory, or such mathematical formalisms have now been successfully applied to different aspects of real life decision making: psychological experiments, decision making in financial markets, legal decision making (a very new development). A pioneering text in this field is by Busemeyer and Bruza as in the references below. .
 Hilbert space is the state space where states and operators describing the system exists, it is a generalization of linear vector spaces, basically a complex, sesqulinear, Normed vector space, where an inner product is defined.
 Born’s rule states that the probability of obtaining one of the states from the initial superposition of states is given by the square of the amplitude (generally complex) for that state, this rule is the basis for computation in quantum theory.
Modeling social dynamical systems
The other sub set of study is applying mathematical or conceptual formalisms in different social dynamical systems. What we mean here is a system with many interacting parts, which evolves over time. For example, stock markets, or say post poll alliances between political parties, or say even more complicated ecological systems.
Agent based modelling is also a central concern for standard utility framework-based modeling, but multiple types of interactions between any number of stakeholders in a social system is very complicated if not impossible to capture via standard models. There is then a traditional ‘representative’ agent modelling bias still present, where all rational agents are considered homogenous and constrained utility maximizers, without enough scope of introducing different types of heterogeneity in sub sets of agents interacting with each other. Also, as some related disciplines like Complexity theory and Econphysics have shown, economy and also society as a whole can not be fully described as a general equilibrium system.
Some researchers such as Fabio Bagarello have demonstrated that such limitations can be up to a good extent resolved using formalism which is widely used in quantum field theory. The so called ‘operator’ formalism used in quantum field theory is a mathematical language developed for analyzing systems with very large degrees of freedom. More specifically such a formalism is called as ‘ladder operator’ approach, where we build up the description of the system based on very simple mathematical objects known as raising and lowering operators. Such operators if acted upon say the vacuum state of a system (say for example in our case a state of stock market where no trading is present) higher excited states are resulted (say in our case how many stocks are traded in that instant). Then we just use various interesting algebraic relations between such operators to describe the system, such that different types of interactions between agents, or agents with the general information environment can be described. Finally, we proceed with a so called ‘Hamiltonian’ formulation for describing the time evolution of such a system.
As of now many numerical analysis or simulation results have provided good evidence of superior analyzing power of such a formalism. There are some other alternative formalisms available too, for example see the seminal book by Baaquiee Belal in the ref.
Way forward for us
We have just touched upon a few areas where quantum formalisms have been used with ongoing success and also evolution of the modellings themselves. For example, one of our main tasks is to apply our formalisms according to complex social systems, for which we need to deviate a lot from standard practices done in the domain of physics. Our language must speak of the social or ecological world which we like to decode. Our models then can provide critical feedbacks for policy makers to plan better strategies for battling pressing issues. At CEASP we are establishing world class collaborations to help define the way forward. Areas like SDG goals, or Policy making in deeply uncertain times, holistic policy making using ecology of mind, are central themes where quantum social science can contribute in understanding the underlying dynamics better.
REFS Haven, Emmanuel and Khrennikov, Andrei (2013), ‘Quantum Social Science’ Cambridge University Press.
Haven, Emmanuel, Robinson, Terry, and Khrennikov, Andrei, (2017), ‘Quantum methods in social science’, World Scientific.
Bagarello, Fabio, (2019), ‘Quantum concepts in Social, Ecological and Biological Sciences’, Cambridge University Press.
Busemeyer, J and Bruza, P (2012), ‘Quantum Models of Cognition and Decision’, Cambridge University Press Khrennikov, Andrei (2010), ‘Ubiquitous Quantum Structure’, Springer.
Belal, Baaique, (2015), ‘Quantum Field Theory for Economics and Finance’, Cambridge University Press.
Why the work of CEASP is important in addressing the wicked problems of today’s world
By Tanya Rana, Candidate of M.A. Public Policy
In the inaugural address of Jindal School of Government and Public Policy’s new Centre – Centre for Complexity Economics, Applied Spirituality and Public Policy (CEASP), the “father of Complexity Economics” – W. Brian Arthur[i] – provided insights on the economic system as a system which is “open to change”, compared to the underlying mechanistic view defined by equilibrium thinking. From the ecology to food, political, or financial systems, the settings within which these systems operate are dynamic, interdependent, and non-linear, meaning that there exist “systems within systems within systems, and so on”[ii]. The agents forming a part of these complex systems “react to the patterns they together create, and that pattern alters itself as a result, causing the agents to react anew”. Economic Complexity critiques mainstream and non-equilibrium way of thinking as it filters exploration, creation, and transitory phenomena of adjustment, adaptation, innovation, and the history itself[iii]. Some of our pertinent public policy challenges can also be tackled through the lens of Complexity. Case in point is the COVID-19 pandemic, where inequities in our health and other social systems, severe economic inequalities, and inability of large swathes of society to cope and recover, have blatantly resurfaced. How should we then address public problems?
Addressing wicked problems through public policy process
The term “wicked problem” was introduced in 1973 by two design theorists namely Horst Rittel and Melvin Webber to highlight the “complexities and challenges of addressing planning and social policy problems”. Real-world wicked problems of the day such as climate change or deviation of financial markets’ performance from their real economies, causing bubbles and crashes, present no easy solutions because of their uniqueness, indeterminate formulation, and so on[iv]. The patterns, arising out of individual behaviours or existing patterns that create incentives for such behaviours are ever evolving, necessitating a nuanced approach to understand these “networks of interactions”.
In a liberalised India, GDP per capita, as the primary objective for public policy making, has tainted our development vision. This has been laid bare with the incidence of the current pandemic, where millions have either been pushed into poverty and destitution or had no recourse in the first place. Post-growth[v] theorists argue that the relentless pursuit of GDP growth as the primary objectives of public policy is inequitable, leading to accumulation of capital in the hands of the few and widening the gaps between the haves and have nots. This gives rise to questions such as: Have societies grown too fast too soon?; What has been the opportunity cost of rampant industrialisation, and ever expanding consumption, and production levels? The concerns of widespread natural disasters, melting of glaciers, forest fires, species extinction, and a climate emergency, reverberate across the existing social and economic inequalities, getting pronounced with time and casting a long shadow on our apparent advancement. These resulting crises interact to produce even more wicked and complex problems which cannot be addressed with our public policy tools such as cost benefit analysis alone. The lens of Complexity is therefore critical to the creation of self-organised, open, democratic, and coordinated systems[vi], where communities can take lead in policy formulation process and not just react to policies or interventions as an “effect” to the “cause” imposed on them.
Role of the Centre
CEASP, in its ambition to move beyond the dominant equilibrium thinking, will study the complexities and interlinkages between social, environmental, political, financial, cultural, and various other dimensions. Thus, the Centre will approach these issues through its three mainstreams of work: a) complexity and public policy; b) quantum social science and public policy; and c) applied spirituality and public policy.Wicked problems, in the age of Anthropocene, are our own creation and the current ways of organising, and interacting are not sustainable. We need an overhaul in our approach, from traditional close systems to open systems, and “work with the relations between the parts which form the whole emergent outcome”. The Centre will coalesce insights from various disciplines, but more importantly, promote a change in consciousness, demonstrating the profundity of human ingenuity.
[i] Complexity Economics was conceptualized in 1987 by a small team at the Santa Fe Institute led by W. Brian Arthur
[ii] As described by Brian Arthur during the inaugural session on September 23, 2020. https://www.youtube.com/watch?v=1Lbc88Xvxls&feature=youtu.be.
[iii] W.Brian Aruthur on Economic Complexity, arguing that non-equilibrium is the natural state of the economy. http://tuvalu.santafe.edu/~wbarthur/Papers/Comp.Econ.SFI.pdf.
[iv] Rittel and Webber underlined 10 important characteristics of wicked problems. https://www.stonybrook.edu/commcms/wicked-problem/about/What-is-a-wicked-problem.
[v] “Post-growth’ is a worldview that sees society operating better without the demand of constant economic growth. It proposes that widespread economic justice, social well-being and ecological regeneration are only possible when money inherently circulates through our economy.” https://www.postgrowth.org/about-post-growth-economics
[vi] Public Problem Solving: https://www.notion.so/Public-Problem-Solving-087f847901eb4cc2856b27a39b3e1871
Quantum-like modelling and complex adaptive systems: policy research implication
By: Professor Sudip Patra Executive deputy director, CEASP, JSGP
Since the last decade there has been a high rise of interest in so called quantum-like paradigm in decision science, with applications in social science, for example in economics, finance and political science. Quantum-like modelling is based on the mathematical and conceptual features which are also prevalent in quantum science (quantum mechanics and quantum field theory), however, this similarity is rather not suggestive of genuine quantum physics of human behavior, let alone social systems. Mainly cognitive scientists (Haven and Khrennikov, 2013) have performed voluminous data analysis based on such quantum-like models, to suggest that human cognition or choice making in particular under contexts like uncertainty, actually can be better described by such models as compared to extant/ still used neoclassical decision models.
For example we may take examples of two different random walk models: Markov random walk model, and quantum-like random walk model. While both these models are used for predicting choice making by decision makers under different interesting contexts: sequential choice making, or joint choice making for instances, the underlying assumptions and mathematical frameworks are very different.
Markov models are based on the assumption that decision makers themselves always have full knowledge about their preference states, it is the modeler who don’t have full knowledge of such preferences and thus must work with ‘subjective’ probability distributions over such preferences. Such models are based on so called axioms of classical probability theory (Kolmogorov axioms).
Quantum random walks are also stochastic in nature, but rather holds that decision makers themselves have inherent uncertainties about some preference states. For example if the decisions are about feelings or say made under uncertain information atmosphere. Such inherent uncertainties are not well described in Markovian framework, hence a quantum-like framework is warranted. Here preference states are represented as ‘super-positions’ of preferences or beliefs, with a different kind of mathematical modelling than ‘set’ theory used in last kind of models. Often such mathematics is termed as Hilbert space modelling.
Now, recently, cognitive scientists (Epping Et al, 2021) have found that it might be more productive to have a hybrid of Markov and quantum-like modelling, where both epistemic / ignorance probabilities as well as inherent or objective uncertainties can be accommodated.
Complex adaptive systems can well be the suitable platforms where such hybrid decision models can be used. Why? Since complex adaptive systems mean by definition interaction between myriads of agents, who have completely different types of knowledge. For example consider an economy, where we have millions of real time decision makers, as well as regulators and policy makers who would influence such decision making. Now for regulators it is vital to have inputs from agents about their preferences, where there obviously would be ‘ignorance’ about full information regarding such preferences. Hence epistemic uncertainty. Again in many contexts decision makers themselves would be uncertain about their on preference states: deeper/ ontic uncertainty. Hence when such actors interact with each other there would be a need to develop a framework comprising both such uncertainties. Hybrid models suggested might be a better framework, which might inform policy makers better compared to stand alone Markov or quantum-like models.
Ontic or epistemic uncertainties?
The debate between ontic or epistemic nature of uncertainty goes back well into the foundations of both social and natural sciences. In classical Physics for example, we mainly model ‘ignorance uncertainty’ which would mean modeler has lack of complete information regarding the initial conditions of the system, among various other possibilities. Bayesian scheme of probability updating is suitable in such models. Bayesian updating would also mean a subjective perspective of uncertainty. In economics J M Keynes adapted such a view for uncertainty.
However, at least orthodox QM would hold that nature can be truly stochastic at the fundamental level, which means uncertainty ultimately might be objective and deeper than subjective degree of beliefs. Complex adaptive systems, as many pioneers like W B Arthur would hold, exhibits such deep uncertainties. Hence the relevance of both Bayesian and quantum-like modelling in such a context. Quantum-like modelling is technically better placed to describe ontic uncertainty, and describe certain outcomes based on behaviors under such uncertainty contexts.
Relevance for policy research
Both complex adaptive systems and quantum-like modelling views would introduce novel shifts in the way extant policy making is done, since policy makers / scholars are generally motivated or have to rely upon extant neoclassical economic thinking. Such frameworks are based on common knowledge of rationality, no uncertainty, and perfect forecasting abilities of agents among other assumptions. However if we base policy making on the perspective that economy is an evolving complex system, then such policy making have to be based on concepts of uncertainties: subjective as well as ontological. Hence comes the implications of quantum-like modelling.
Already research works are being done in the same direction, for example choice modelling center at university of Leeds UK has employed quantum-like modelling for describing decision making for transportation choices under uncertainties.
At CEASP, JSGP, research is ongoing on how to employ quantum-like modelling to inform policy making in Indian contexts.
Haven, Emmanuel, and Khrennikov, Andrei, (2013), quantum social science, CUP.
SANTA FE institute conference proceedings.
Published at CEASP’s LinkedIn: https://www.linkedin.com/pulse/quantum-like-modelling-complex-adaptive-/?trackingId=RNolmeOhOyMmWCq0SACAcQ%3D%3D
Nobel Prize for Complex systems With a simple message Dr Sudip Patra
Nobel Prize for Physics 2021 has put complex systems research on the top of most pressing research areas. Complex adaptive systems are unequivocally important now, whether weather forecasting, climate change and its implications for daily living, understanding microphysical processes in materials, or various consequences of such for social dynamical systems. For example, how such understandings might impact policy making? Policy making in a complex society (Arthur et al, 2019) has already started delving into depths of complexity science.
First, we remind ourselves of a few basic concepts before exploring the current Nobel Prize. Complex adaptive systems does not mean complicated systems as the common usage of the words go. At times Scientists (for example think of molecular Biology, or say Biophysics) do model a composite system made up of correlated sub systems, such that the composite system’s features cannot be simply understood by studying the subsystems separately. It is only when whole is studied parts become relevant in the context of the whole. Such systems can be called as complex systems. A dynamic social system, for example, a well-organized market, can be thought in the same manner. There are certain critical features of complex systems, for example, climate or economy as a whole; such features are: deep uncertainty rather than predictability based on some simplified framework, for example ‘Newtonian’ Mechanistic framework, disequilibrium in general, emergence at the meso and macro levels, feedback loops to name some.
Another related and very deep concept is of uncertainty itself, is all uncertainty ignorance? Or can there be objective uncertainty which can never be done away with information updating? Ignorance uncertainty / subjective credence is very well studied in Bayesian statistics for example, whereas fundamental uncertainty is thought to be related to Quantum Physics. Complex adaptive systems may exhibit both types of uncertainties. Hence the question which has haunted scientists for ages across disciplines is how to navigate or survive or analyze in a complex world with such uncertainties?
Particular contributions (WINNERS: SYUKURO MANABE, K H MANN, and GEORGIO PARISI)
Earth’s Climate system and change: Syukuro Manabe demonstrated how increased levels of carbon dioxide in the atmosphere lead to increased temperatures at the surface of the Earth. In the 1960s, he led the development of physical models of the Earth’s climate and was the first person to explore the interaction between radiation balance and the vertical transport of air masses. His work laid the foundation for the development of current climate models.
About ten years later, Klaus Hassel Mann created a model that links together weather and climate, thus answering the question of why climate models can be reliable despite weather being changeable and chaotic. He also developed methods for identifying specific signals, fingerprints that both natural phenomena and human activities imprint in the climate. His methods have been used to prove that the increased temperature in the atmosphere is due to human emissions of carbon dioxide.
Complex Materials: Around 1980, Giorgio Parisi discovered hidden patterns in disordered complex materials. His discoveries are among the most important contributions to the theory of complex systems. They make it possible to understand and describe many different and apparently entirely random materials and phenomena, not only in physics but also in other, very different areas, such as mathematics, biology, neuroscience and machine learning.
“The discoveries being recognised this year demonstrate that our knowledge about the climate rests on a solid scientific foundation, based on a rigorous analysis of observations. This year’s Laureates have all contributed to us gaining deeper insight into the properties and evolution of complex physical systems,” says Thors Hans Hansson, chair of the Nobel Committee for Physics.
For technical details and further self-study please refer to below:
What we may learn and do?
CEASP, complexity economics, applied spirituality and public policy center, is based on the ethos of holism. To take a leaf out of David Bohm’s world of works, we view the world as an undivided universe. Certainly, there are various scientific methodological challenges to reckon with. The current Nobel Prize is in recognition of such novel methodological paradigms. They provide tools in hands of budding complexity scientists (across disciplines) to extend in their own research areas. Here comes our own challenge at CEASP, since we are focused on Policy implications, we need to assimilate Policy methods and Policy makers’ thought processes in the grand complexity architect. We need to realize social systems have their own complexity features which might be even harder or at least distinct than say microphysical processes in materials. In societies we create our own realities, which in turn feedback upon us.
CEASP has been organizing interdisciplinary expert led seminars, conferences and focused reading groups since its inception. We have plans in widening our networks world-wide, and also critically reach out to students, policy researchers and real policy makers, focused in Indian context. We plan to roll out both in campus and online programs on complex adaptive systems.
However, we can’t wrap up this Blog without mentioning the most critical ingredient of our approach at CEASP. Though this Nobel Prize has given us enough courage to march on, there is still one essence missing. To quote late Stephen Hawking ‘who breathes fire into the equations?’ well we would love to be secular here, but also refer to holism promoted by spiritual traditions. Even modern science (Rovelli, 2020) from quantum mechanics to cosmology have been deeply moved by traditions such as Sunnyavada of Madhyamika Buddhism. Hence we strive for reaching out to Secular Spiritual thinkers, to help build bridges among people of different walks of life.
Hence our simple message to take from this Prize on complexity would be CHAREI BETI CHAREI BETI… roughly from original Sanskrit meaning just Move On, but with good intentions.
Arthur, Brian, Beinhocker Erric and Stanger Allison (editors), (2019), COMPLEXITY ECONOMICS, SFI PRESS.
Rovelli, Carlo, (2020), ‘Helgoland’, Penguin.
 Which means if someone provides you with initial conditions of a system like say two billiard balls: position and momentum of two balls at time t=0, and you know the exact dynamical laws, then ceteris paribus, you might fully predict their evolution in time and space ad infinitum. If you want you might extend this argument to all possible particles in the universe, and think of a Demon with virtually infinite computation power: result would be full prediction of evolution of universe as a whole! In this story there is NO deep or fundamental uncertainty.
 There are two types of emergence concepts: week emergence where it is always possible in principle to reduce the emerging properties to its fundamental ingredients, and strong: where emerging properties can never be reduced to its constituents: for example CAN macroeconomics be derived from micro economics? Still an open question.
Published at CEASP’s LinkedIn: https://www.linkedin.com/pulse/nobel-prize-complex-systems-simple-/?trackingId=XQ4D3UCIXoyJukjZnwDdnw%3D%3D
Quantum-like Modelling paradigm
Possible inputs to policy making
Abstract: Quantum-like paradigm is an interface between mathematical or information theoretic tools widely used in quantum theory, and decision science. Over the last decade QLM (quantum-like modelling) has proved to be quite successful in describing human cognition, particularly, in contexts of uncertainty and ambiguity. QLM has been able to provide a more comprehensive non-Boolean decision framework, which describes various ‘anomalies’ or deviations of cognition processes from the standard Boolean logic based predictions. QLM has been applied to multiple areas, viz, financial market modelling to game theory, and is growing stronger. But what possible lessons can policy scholars and practitioners may draw from such a novel paradigm? QLM has been applied in various fields since then, cognitive models, visual perceptions, financial market modelling, and game theory, to name a few relevant areas. In the current article we would like to explore then the possible contribution which quantum-like modelling might make to behavioral policy making, since it is becoming more critical to re-orient policy making and studies to real behavior in contexts such as financial markets. The current article is aimed as a preliminary discussion in the very direction. Specifically we focus on the social contagion problems, which have direct consequences for policy makers.
Key words: quantum-like modelling QLM, behavioral policy making, Hilbert space modelling, Complex adaptive systems (CAS), Uncertainty, heterogeneity, social contagion
Policy research literature is evolving dramatically and is adapting different interdisciplinary paradigms as inputs to designing ever more comprehensive policy frameworks. Behavioral policy making (1) can be referred to as one such emerging direction. Certainly, behavioral science at large and behavioral economics or finance in particular have inspired such directions. Thaler’s original thesis on Nudge theory (2) or Shiller’s narrative economics (3) have already been incorporated in policy making exercises. On the other hand complex adaptive systems approach (4) which perceives economy as dynamically evolving complex system with deep uncertainties and features like emergence and self-organizations, has been incorporated in policy designs currently (5).
Given this exciting backdrop of foundational thinking in policy domain, another new paradigm, the often called ‘quantum-like’ paradigm of decision modelling might also play interesting roles. Quantum-like paradigm of cognition or decision modelling is not to be perceived as suggestion for reductionism, or reducing cognition to quantum physics. Rather quantum-like modelling (6) is extension of deep philosophical and mathematical concepts widely used in quantum science, to the domain of cognition, particularly in the contexts of uncertainty and ambiguity.
Voluminous literature on quantum-like modelling applications in financial decision making , as well as in areas of political science (7) and in the new area of quantum games (8), suggest that new insights might be generated by this paradigm for social science at large and policy designing in particular. The current write up aims at exploring or highlighting some of the ongoing works already, across countries as well as in Indian context.
- Philosophical roots:
Philosophical roots to quantum-like paradigm goes back to foundations of quantum mechanics, at least to 1930s. Bohr (11) particularly was very curious about striking analogies between human cognition and formalisms of quantum theory, particularly, ideas of contextuality and complementarity. Contextuality by default suggests that results of observations, whether natural or cognitive science are directly influenced by the context in which such observations are being done. Bohr defined context as an undivided whole between the observed system / phenomenon and its environment comprising of any observer and the larger atmosphere. This idea got suppressed when Heisenberg (12) later introduced the concept of ‘cut’, which would mean for QM that above that hypothetical cut/ scale world is ruled by classical physical laws and below only quantum rules prevail. There has been a dense literature on Heisenberg cut, and particularly Bohr was unhappy about the framework.
Bohm-Hiley (13) later on extended from Bohr’s perspectives and built a complexity approach of life as a whole, where too it was noted that thought processes may also exhibit some general uncertainty relations as Heisenberg’s celebrated uncertainty principles showed.
Andrei Khrennikov (14) in modern era proposed a general quantum-like framework based on contextuality as a central feature, which could be applied to cognition and social science decision making in general. Authors later (15) have developed quantum-decision theory, which is particularly dedicated to describe decision making under uncertainty.
In social science also there is a dense literature on uncertainty, particularly, J M Keynes and Ramsey (16) intensely debated on nature of uncertainty in economics, while the former was more inclined towards accepting uncertainty as subjective credence related, Ramsey was more accommodative of deeper or ontological uncertainty. Bayesian decision making paradigm is fully based on subjective probability perspective, and has been hugely successful in social sciences. However a voluminous literature (17) show that such frameworks might not describe decision making under deeper uncertainty contexts. Difference can be understood if we take perspectives of both decision maker and a modeler of decision making (18). While the decision maker might have uncertainty about their own decision states (hence ontological uncertainty), a modeler might be ignorant about the true decision state of the decision maker (hence epistemic or subjective uncertainty). Now in a complex adaptive system, like economy with both real decision makers and policy designers as modelers included there might be combination of both type of uncertainties.
Hence cognitive scientists hold that both Bayesian and Quantum-like modelling, so called hybrid models might be efficient in describing real decision making in a complex system.
1.2 Some mathematical preliminaries or concepts:
Though we are presenting a non-technical summary of quantum-like paradigm here, it is worthwhile to point out that there are subtle differences between the mathematical logical structures of neoclassical decision theory and quantum-like decision theory. While the former is grounded on set theory and in general ‘Boolean’ logic, the latter is based on Hilbert space modelling which can be thought of compatible with a more general ‘Non-Boolean’ logic. Hilbert space being a complex linear vector space, which assures that linear ‘super-positions’ of basis states are also legitimate states. Now linear super-positions are not classical probability mixtures, of say 50% chance of one basis state (say heads) and 50% chance of another basis state (say tails), rather it can never be described in classical probabilistic terms. Such a description can describe better the ‘ontological’ uncertainty state. Quantum-like framework can be viewed as a probability calculus scheme also, where till the system is observed / measured it remains as a linear super-posed states of bases, only when measurement occurs do such a sate reduces / collapse to a particular possibility.
Quantum-like framework then provides the unique and consistent way to calculate such probabilities, often called as ‘Born’s’ rule. The general mathematical framework is more comprehensive, and allows for more general states, the above mentioned states are called ‘pure states’, where as if there a probability distribution over such pure states we have ‘mixed states’, in technical literature such states are called as ‘density matrices’. Hence pure states can represent ‘ontological’ uncertainty, whereas ‘density matrices’ represent the ignorance over such pure states. If the former can represent decision maker’s uncertainty about their own state of choice, the latter can represent modeler’s ignorance about decision maker’s state (19).
Though there are different ways of modelling decision states using a Hilbert space set up, commonly a decision maker’s cognitive state is first represented as a ray in such a finite dimensional complex linear vector space.
- Policy implications: behavioral and methodological contributions
- Applications for social sciences in general
There has been a voluminous literature on applications of quantum-like modelling in social sciences. Here we mention the main directions pointwise below.
- Decision making models: where contextuality plays a central role, there is a deep overlap between behavioral economics and quantum-like models here.
- Financial market models: many cognitive biases, effects like diversity of investors’ opinion on asset prices (20), modified Black-Scholes formulation (21).
- Political science: QLM used in describing mood swings of voters, or preference reversals using real data (22)
- Legal decision making: a budding literature where QLM can be used in describing cognitive biases in legal decision making processes.
We now explore the possible contributions which QLM might make in a complex adaptive systems approach to policy making.
2.2 Complex adaptive systems approach to policy making and quantum-like modelling
Complex adaptive systems approach to policy research (as cited earlier) has been in focus recently. Complex adaptive systems, for example, macro economy as a whole, is an ever evolving, at times far from equilibrium system, comprising of heterogeneous agents or decision makers, containing deep uncertainty. Such systems would allow for novel emergences, such collective behavioral patterns which are very sensitive to initial conditions and hard to predict (Butterfly effect is a metaphor here). CAS approach has been well assimilated into economic theory now (as cited earlier), with complexity economics movement, hence policy research can be significantly enriched with inputs from CAS.
Since CAS approach is foundationally based on realistic heterogeneous behaviors of decision makers, quantum cognition or quantum-like modelling paradigm might duly contribute. CAS approach (for example Santa Fe artificial stock market models, or ‘agent zero’ model suggested recently)holds that individual agents are comparable to computer programs which are different from each other, and then such ‘computer programs’ interact with each other, learn from each other and evolve. While evolving they reject unsuitable ideas (which may be different forecasting models they start with with), and adapt to more suitable ideas. Hence decision makers live in an ‘ecology’ of models, certainly we can see a Darwinian picture evolving.
However how such ‘computer programs’ can be built in a more realistic and comprehensive manner? QLM may provide a more comprehensive framework for building individual decision making / forecasting models, which would then create an ‘ecology’ of models for competing and evolving. Since one advantage of QLM is that it need not be a total shift from constrained utility optimizing models, rather under assumptions of no uncertainty standard results would still prevail. Also there are new ‘contextuality’ utility frameworks proposed (23), where contexts in which optimizations are done also have a direct influence on the final preference patterns in such contexts.
Another critical holistic aspect is uncertainty itself, as mentioned earlier, in natural sciences too we can distinguish between two concepts: ontological and epistemological uncertainties. Authors (as cited earlier) have recently proposed hybrid modeling, where both decision maker’s ontic uncertainty state as well as modelers epistemic uncertainty state about decision makers uncertainty states, can be comprehensively used in a single coherent framework. Ontological uncertainty, can be evidently better described in a QLM set up, for example in a simplistic set up if mental or cognitive states of agents are modelled as ‘rays’ in finite dimensional complex linear Hilbert space, we have based on ‘linearity’ property of Hilbert space, that linear superposition of basis states are also legitimate states. Such superposed states are basic description of an ontic uncertain state, which can never be compared with classical probabilistic mixes of states, they are also termed as pure states. Epistemological uncertainties are by the way modelled by Markovian models. QLM also allows for modelling interactions between decision makers’ cognitive states with wider information environment (24), where so called GKSL master equations are used.
- Social contagion modelling and quantum-like approach: policy implications
We now focus on a particular fertile area of research, social contagion namely, which has been studied from different perspectives. Both behavioral economics literature (for example, Robert Shiller’s seminal works on narrative economics) as well as complexity economics (referring to seminal computational or agent based models of Santa Fe for example) have developed relevant frameworks. The central ideas being how some opinions, or narratives, or ideas get viral in society and impacts real economy? Which might be the underlying behavioral factors which make some narratives linger more than others? How heterogeneous agents respond and spread such narratives?
Shiller () provides an interesting reference to Lafer curve model in macroeconomics, such a narrative which proposed a non linear relationship between corporate taxation level and the revenue generation for Govt. That framework got currency during late 70s when Ronal Regan in US and Margaret Thatcher in UK were pushing very hard for neo-liberal reforms. However even such a framework as a narrative had a short life as a social contagion, waning since late 90s, and during the early 2000s when develop world was suffering from dot com crash and then on recurrent crises, Laffer curve narrative has nearly withered away. Shiller raises the possibility whether such arousal, peaking and waning of social contagions might be modelled with the help of well-known epidemiological models. Epidemiological models () have been successfully deployed in medical research since late 1920s, however direct extension of such models in social contagions might not be wise, since societies suffer deep uncertainties and very much heterogeneous agents.
- Concluding remarks
Policy research in it-self has emerged as a new field of study, autonomous as well as very interdisciplinary. Though standard policy making frameworks are still based on Neo-classical frameworks, there is a strong inclination towards behavioral policy making (29, 30) and complex adaptive systems approach. Quantum cognition or quantum-like modelling paradigm is not in conflict with either behavioral or complexity modelling, rather can constructively provide insights to them, and co-evolve. There are both deep philosophical as well as methodological insights we can derive from QLM. On the philosophical front we still need to work on a holistic theory based on comprehensive decision making frameworks, and on the methodological front there can be interesting hybrid models which imbibe both quantum-like and neo-classical concepts.
- Jones, B. D. 2017. “Behavioral Rationality as a Foundation for Public Policy Studies.” Cognitive Systems Research 43: 63–75
- Thaler, R. H. (2018). From cashews to nudges: the evolution of behavioral economics. Am. Econ. Rev. 108, 1265–1287.
- R. Shiller, Narrative Economics: How Stories Go Viral and Drive Major Economic Events
Princeton University Press (2019)
- Arthur WB (2013) Complexity Economics: A Different Framework for Economic Thought. Santa Fe Institute Working Paper.
- Durlauf, Steven. “What Should Policymakers Know About Economic Complexity?” 1Available at https://ideas.repec.org/p/wop/safiwp/97-10-080.html.
- Haven, Emmanuel and Khrennikov, Andrei (2013), Quantum Social Science, CUP.
- As 6.
- Patra, S and Ghose, P (2020), Quantum-like modelling in game theory, Asian Journal of Economics and Banking.
- Penrose, Roger (1989), Emperor’s new mind, OUP.
- See Max Tegmark’s critique of the same, MIT.
- Bohr, N. (1987 reprint). Essays 1933 to 1957 on atomic physics and human knowledge (The philosophical writings of Niels Bohr: Vol. II). New York: Ox Bow Press.
- Atmanspacher, H., 2014, “20th century variants of dual-aspect thinking (with commentaries and replies),” Mind and Matter, 12: 245–288.
- Atmanspacher H. The Pauli-Jung conjecture and its relatives: a formally augmented outline. Open Philos 2020;3:527–49.
- Rafaï, I., Duchêne, S., Guerci, E. et al. The triple-store experiment: a first simultaneous test of classical and quantum probabilities in choice over menus. Theory Decis 92, 387–406 (2022).
- Didier Sornette 2014 Rep. Prog. Phys. 77 062001
- CARABELLI, A.M. 1985, Keynes on Cause, Chance and Possibility, in Lawson T. and Pesaran H. eds., Keynes’s Economics: Methodological Issues, New York, Sharpe, 151-18.
- Busemeyer, J. R., Pothos, E. M., Franco, R., & Trueblood, J. S. (2011). A quantum theoretical explanation for probability judgment errors. Psychological Review, 118(2), 193–218.
- Epping, G., Kvam, P. D., Pleskac, T. J., & Busemeyer, J. R. (2022, February 2). Open System Model of Choice and Response Time. https://doi.org/10.31234/osf.io/frq96
- Same as 18.
- F. Bagarello, A quantum statistical approach to simplified stock mar- kets, Physica A: Statistical Mechanics and its Applications, 388(20):4397-4406 (2009).
- B. E Baaquie, Path Integrals and Hamiltonians: Principles and Methods. Cambridge University Press, (2014).
- Khrennikova P, Haven E. 2016 Instability of political preferences and the role of mass media: a representation in quantum framework. Phil. Trans. R. Soc. A 374, 20150106.
- Aerts, D., & Sozzo, S. (2013). A contextual risk model for the Ellsberg paradox. Journal of Engineering Science and Technology Review, 4, 246–250.
- Haven, E, Khrennikov, A. (Eds.), 2017a. The Palgrave Handbook of Quantum Models in Social Science. Applications and Grand Challenges. Palgrave Maxmilan UK.
 Though certainly there have been proposals (9) to explore emergence of brain consciousness and cognition from underlying genuine quantum physical processes, but for our purpose this literature may not concern us, also there are counter suggestions (10).
 Measurement is a very loaded and dense literature of interpretations of QM is related to such a term, here we might refer to any interaction with the ‘superposed’ initial ‘belief state’ of a decision maker, for example when a specific question is posed to the decision maker and they make a final decision, which would mean in this picture : collapse of the linear super-position state to one of the possibilities, or further updating which is often termed as ‘channeling’.