A rational choice framework for collective behavior

As the world becomes increasingly digitally mediated, people can more and more easily form groups, teams, and communities around shared interests and goals. Yet there is a constant struggle across forms of social organization to maintain stability and coherency in the face of disparate individual experiences and agendas. When are collectives able to function and thrive despite these challenges? In this thesis I propose a theoretical framework for reasoning about collective intelligence—the ability of people to accomplish their shared goals together. A simple result from the literature on multiagent systems suggests that strong general collective intelligence in the form of “rational group agency” arises from three conditions: aligned utilities, accurate shared beliefs, and coordinated actions. However, achieving these conditions can be difficult, as evidenced by impossibility results related to each condition from the literature on social choice, belief aggregation, and distributed systems. The theoretical framework I propose serves as a point of inspiration to study how human groups address these difficulties. To this end, I develop computational models of facets of human collective intelligence, and test these models in specific case studies. The models I introduce suggest distributed Bayesian inference as a framework for understanding shared belief formation, and also show that people can overcome other difficult computational challenges associated with achieving rational group agency, including balancing the group “exploration versus exploitation dilemma” for information gathering and inferring levels of “common p-belief” to coordinate actions. Thesis Supervisor: Joshua B. Tenenbaum Title: Professor of Brain and Cognitive Sciences Thesis Supervisor: Alex “Sandy” Pentland Title: Toshiba Professor of Media Arts and Sciences

[1]  Kevin Crowston,et al.  What is coordination theory and how can it help design cooperative work systems? , 1990, CSCW '90.

[2]  Michael E. Bratman,et al.  Shared Cooperative Activity , 1991 .

[3]  Samuel J. Gershman,et al.  Computational rationality: A converging paradigm for intelligence in brains, minds, and machines , 2015, Science.

[4]  Charles Kemp,et al.  Bayesian models of cognition , 2008 .

[5]  S. Milgram,et al.  Note on the drawing power of crowds of different size. , 1969 .

[6]  J. Tenenbaum,et al.  Optimal Predictions in Everyday Cognition , 2006, Psychological science.

[7]  Thomas T. Hills,et al.  Exploration versus exploitation in space, mind, and society , 2015, Trends in Cognitive Sciences.

[8]  Sean J. Taylor,et al.  Social Influence Bias: A Randomized Experiment , 2013, Science.

[9]  Polly S Nichols,et al.  Agreeing to disagree. , 2005, General dentistry.

[10]  Pedro A. Ortega,et al.  A Unified Framework for Resource-Bounded Autonomous Agents Interacting with Unknown Environments , 2011 .

[11]  J. Henrich,et al.  The cultural niche: Why social learning is essential for human adaptation , 2011, Proceedings of the National Academy of Sciences.

[12]  John W. Payne,et al.  Task complexity and contingent processing in decision making: An information search and protocol analysis☆ , 1976 .

[13]  Nisheeth K. Vishnoi,et al.  A Distributed Learning Dynamics in Social Groups , 2017, PODC.

[14]  Soong Moon Kang,et al.  Field experiments of success-breeds-success dynamics , 2014, Proceedings of the National Academy of Sciences.

[15]  José Halloy,et al.  Collegial decision making based on social amplification leads to optimal group formation. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[16]  D. Monderer,et al.  Approximating common knowledge with common beliefs , 1989 .

[17]  Ya'akov Gal,et al.  Networks of Influence Diagrams: A Formalism for Representing Agents' Beliefs and Decision-Making Processes , 2008, J. Artif. Intell. Res..

[18]  S. Pratt,et al.  A tunable algorithm for collective decision-making , 2006, Proceedings of the National Academy of Sciences.

[19]  Steven Pinker,et al.  The psychology of coordination and common knowledge. , 2014, Journal of personality and social psychology.

[20]  S. Bikhchandani,et al.  You have printed the following article : A Theory of Fads , Fashion , Custom , and Cultural Change as Informational Cascades , 2007 .

[21]  Amos Korman,et al.  Theoretical Distributed Computing Meets Biology: A Review , 2013, ICDCIT.

[22]  M. Rabin The Experimental Study of Social Preferences , 2014 .

[23]  T. Kameda,et al.  Human Collective Intelligence under Dual Exploration-Exploitation Dilemmas , 2014, PloS one.

[24]  Nir Vulkan An Economist's Perspective on Probability Matching , 2000 .

[25]  Colin Camerer Behavioral Game Theory: Experiments in Strategic Interaction , 2003 .

[26]  Ward Hanson,et al.  Hits and misses: Herd behavior and online product popularity , 1996 .

[27]  Ohad Shamir,et al.  Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation , 2013, NIPS.

[28]  S. Spyrou,et al.  Herding in financial markets: a review of the literature , 2013 .

[29]  Michael Kearns,et al.  Experiments in social computation , 2012, KDD.

[30]  Sarit Kraus,et al.  Collaborative Plans for Complex Group Action , 1996, Artif. Intell..

[31]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

[32]  M. Tomasello,et al.  Understanding and sharing intentions: The origins of cultural cognition , 2005, Behavioral and Brain Sciences.

[33]  Robert X D Hawkins,et al.  Conducting real-time multiplayer experiments on the web , 2014, Behavior Research Methods.

[34]  Long Tran-Thanh,et al.  Efficient Thompson Sampling for Online Matrix-Factorization Recommendation , 2015, NIPS.

[35]  Kate Starbird,et al.  Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking , 2017, CHI.

[36]  Robert L. Goldstone,et al.  Author ' s personal copy Recognizing group cognition Action editor : , 2010 .

[37]  Alex Pentland,et al.  Decoding Social Influence and the Wisdom of the Crowd in Financial Trading Network , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.

[38]  Monika Richter,et al.  Cognition In The Wild , 2016 .

[39]  Leslie A. DeChurch,et al.  Information sharing and team performance: a meta-analysis. , 2009, The Journal of applied psychology.

[40]  S. Mohammed,et al.  Metaphor No More: A 15-Year Review of the Team Mental Model Construct , 2010 .

[41]  Duncan Snidal,et al.  The Game Theory of International Politics , 1985, World Politics.

[42]  I. Couzin Collective cognition in animal groups , 2009, Trends in Cognitive Sciences.

[43]  Jacob G Foster,et al.  Choosing experiments to accelerate collective discovery , 2015, Proceedings of the National Academy of Sciences.

[44]  V. Buskens,et al.  Micro-Macro Links and Microfoundations in Sociology , 2011 .

[45]  Mark Lubell,et al.  Beyond existence and aiming outside the laboratory: estimating frequency-dependent and pay-off-biased social learning strategies , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[46]  Neil Immerman,et al.  The Complexity of Decentralized Control of Markov Decision Processes , 2000, UAI.

[47]  Matthew J. Salganik,et al.  Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market , 2006, Science.

[48]  I. Couzin Collective minds , 2007, Nature.

[49]  Raymond J. Dolan,et al.  Game Theory of Mind , 2008, PLoS Comput. Biol..

[50]  Sarit Kraus,et al.  Agent-Human Coordination with Communication Costs Under Uncertainty , 2012, AAAI.

[51]  Thomas L. Griffiths,et al.  One and Done? Optimal Decisions From Very Few Samples , 2014, Cogn. Sci..

[52]  T. Seeley,et al.  Group decision making in swarms of honey bees , 1999, Behavioral Ecology and Sociobiology.

[53]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[54]  Shipra Agrawal,et al.  Analysis of Thompson Sampling for the Multi-armed Bandit Problem , 2011, COLT.

[55]  D. Meyer,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S6 References Evidence for a Collective Intelligence Factor in the Performance of Human Groups , 2022 .

[56]  M. Arellano,et al.  Computing Robust Standard Errors for Within-Groups Estimators , 2009 .

[57]  M. Degroot Reaching a Consensus , 1974 .

[58]  H. Roche,et al.  Why Copy Others? Insights from the Social Learning Strategies Tournament , 2010 .

[59]  R J HERRNSTEIN,et al.  Relative and absolute strength of response as a function of frequency of reinforcement. , 1961, Journal of the experimental analysis of behavior.

[60]  Floyd H. Allport,et al.  The Group Fallacy in Relation to Social Science , 1924, American Journal of Sociology.

[61]  Ron Sun,et al.  The Cambridge Handbook of Computational Psychology , 2008 .

[62]  Joshua B. Tenenbaum,et al.  Coordinate to cooperate or compete: Abstract goals and joint intentions in social interaction , 2016, CogSci.

[63]  H. Gintis The Bounds of Reason: Game Theory and the Unification of the Behavioral Sciences , 2014 .

[64]  Thomas L. Griffiths,et al.  Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic , 2015, Top. Cogn. Sci..

[65]  J. Ruiz Moreno [Organizational learning]. , 2001, Revista de enfermeria.

[66]  R. Sugden Team Reasoning and Intentional Cooperation for Mutual Benefit , 2014 .

[67]  T. Sargent,et al.  Recursive Macroeconomic Theory , 2000 .

[68]  Joshua B. Tenenbaum,et al.  Feature-based Joint Planning and Norm Learning in Collaborative Games , 2016, CogSci.

[69]  Nicholas R. Jennings,et al.  Human-agent collectives , 2014, CACM.

[70]  E. Durkheim,et al.  Rules of Sociological Method , 1964 .

[71]  Robert L. Goldstone,et al.  Collective Search in Concrete and Abstract Spaces , 2008 .

[72]  W. R. Thompson ON THE LIKELIHOOD THAT ONE UNKNOWN PROBABILITY EXCEEDS ANOTHER IN VIEW OF THE EVIDENCE OF TWO SAMPLES , 1933 .

[73]  Joseph Y. Halpern,et al.  Knowledge and common knowledge in a distributed environment , 1984, JACM.

[74]  G. Haines,et al.  The Theory of Buyer Behavior. , 1970 .

[75]  Noah J. Goldstein,et al.  Social influence: compliance and conformity. , 2004, Annual review of psychology.

[76]  Alex Pentland,et al.  Emergent Collective Sensing in Human Groups , 2015, CogSci.

[77]  James D. Hollan,et al.  Distributed cognition: toward a new foundation for human-computer interaction research , 2000, TCHI.

[78]  Lihong Li,et al.  An Empirical Evaluation of Thompson Sampling , 2011, NIPS.

[79]  M. Tomasello A Natural History of Human Thinking , 2014 .

[80]  M. Tomasello,et al.  Great apes anticipate that other individuals will act according to false beliefs , 2016, Science.

[81]  N. Kerr,et al.  Group performance and decision making. , 2004, Annual review of psychology.

[82]  Matthew O. Jackson,et al.  Naïve Learning in Social Networks and the Wisdom of Crowds , 2010 .

[83]  Sarit Kraus,et al.  Ad Hoc Autonomous Agent Teams: Collaboration without Pre-Coordination , 2010, AAAI.

[84]  Winter A. Mason,et al.  Collaborative learning in networks , 2011, Proceedings of the National Academy of Sciences.

[85]  Robert L. Goldstone,et al.  Collective Behavior , 2002 .

[86]  Vittorio Loreto,et al.  Collective dynamics of social annotation , 2009, Proceedings of the National Academy of Sciences.

[87]  Paul J. B. Hart,et al.  Quorum decision-making facilitates information transfer in fish shoals , 2008, Proceedings of the National Academy of Sciences.

[88]  A. Rubinstein The Electronic Mail Game: Strategic Behavior Under "Almost Common Knowledge" , 1989 .

[89]  C. Chabris,et al.  Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face , 2014, PloS one.

[90]  I. Couzin,et al.  Emergent Sensing of Complex Environments by Mobile Animal Groups , 2013, Science.

[91]  David Lazer,et al.  The Network Structure of Exploration and Exploitation , 2007 .

[92]  Eamonn B. Mallon,et al.  An agent-based model of collective nest choice by the ant Temnothorax albipennis , 2005, Animal Behaviour.

[93]  Daniel A. Levinthal,et al.  Exploration and Exploitation in Organizational Learning , 2007 .

[94]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[95]  M. Kearns,et al.  An Experimental Study of the Coloring Problem on Human Subject Networks , 2006, Science.

[96]  Jack Bowden,et al.  Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges. , 2015, Statistical science : a review journal of the Institute of Mathematical Statistics.

[97]  Alex Pentland,et al.  Bots as Virtual Confederates: Design and Ethics , 2016, CSCW.

[98]  H. A. Schwartz,et al.  Birds of a Feather Do Flock Together , 2017, Psychological science.

[99]  Alex Pentland,et al.  Human collective intelligence as distributed Bayesian inference , 2016, ArXiv.

[100]  Chris Arney Social Physics: How Good Ideas Spread - the Lessons from a New Science , 2014 .

[101]  P. Bearman,et al.  The Oxford handbook of analytical sociology , 2009 .

[102]  Rémi Munos,et al.  Thompson Sampling: An Asymptotically Optimal Finite-Time Analysis , 2012, ALT.

[103]  A. Barabasi,et al.  Bose-Einstein condensation in complex networks. , 2000, Physical review letters.

[104]  K. Arrow A Difficulty in the Concept of Social Welfare , 1950, Journal of Political Economy.

[105]  Stephen Morris,et al.  Approximate Common Knowledge and Co-ordination: Recent Lessons from Game Theory , 1997, J. Log. Lang. Inf..

[106]  D. Wegner Transactive Memory: A Contemporary Analysis of the Group Mind , 1987 .

[107]  Ramamohan Paturi,et al.  Common Knowledge and State-Dependent Equilibria , 2012, SAGT.

[108]  C. List,et al.  Aggregating Sets of Judgments: An Impossibility Result , 2002, Economics and Philosophy.

[109]  G. Stewart A Meta-Analytic Review of Relationships Between Team Design Features and Team Performance , 2006 .

[110]  L. Elisa Celis,et al.  Sequential Voting Promotes Collective Discovery in Social Recommendation Systems , 2016, ICWSM.

[111]  S. Asch Opinions and Social Pressure , 1955, Nature.

[112]  P. Berger,et al.  The Social Construction of Reality , 1966 .

[113]  Jure Leskovec,et al.  From amateurs to connoisseurs: modeling the evolution of user expertise through online reviews , 2013, WWW.

[114]  Alex Pentland,et al.  Modeling Human Ad Hoc Coordination , 2016, AAAI.

[115]  Allen Newell The Knowledge Level (Presidential Address) , 1980, AI Mag..

[116]  Eshcar Hillel,et al.  Distributed Exploration in Multi-Armed Bandits , 2013, NIPS.

[117]  Tim Roughgarden,et al.  Mathematical foundations for social computing , 2016, Commun. ACM.

[118]  C. Chamley Rational Herds: Economic Models of Social Learning , 2003 .

[119]  Edmund H. Durfee,et al.  Decision-theoretic recursive modeling and the coordinated attack problem , 1992 .

[120]  Galen Pickard,et al.  Quantifying Social Influence in an Online Cultural Market , 2012, PloS one.

[121]  Robert L. Goldstone,et al.  Social Learning Strategies in Networked Groups , 2013, Cogn. Sci..