Cognitive science meets multi-agent systems: A prolegomenon

In the current research on multi-agent systems (MAS), many theoretical issues related to sociocultural processes have been touched upon. These issues are in fact intellectually profound and should prove to be significant for MAS. Moreover, these issues should have equally significant impact on cognitive science, if we ever try to understand cognition in the broad context of sociocultural environments in which cognitive agents exist. Furthermore, cognitive models as studied in cognitive science can help us in a substantial way to better probe multi-agent issues, by taking into account essential characteristics of cognitive agents and their various capacities. In this paper, we systematically examine the interplay among social sciences, MAS, and cognitive science. We try to justify an integrated approach for MAS which incorporates different perspectives. We show how a new cognitive model, CLARION, can embody such an integrated approach through a combination of autonomous learning and assimilation.

[1]  D. Spalding The Principles of Psychology , 1873, Nature.

[2]  William B. Weeden,et al.  Institutions and economics , 2022 .

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

[4]  Sigmund Freud,et al.  A general selection from the works of Sigmund Freud , 1937 .

[5]  C. Mills,et al.  The Theory of Social and Economic Organization , 1948 .

[6]  A. Schutz The phenomenology of the social world , 1967 .

[7]  T Shallice,et al.  Dual functions of consciousness. , 1972, Psychological review.

[8]  E. A. Thomas,et al.  On the dynamics of two-person interactions , 1979 .

[9]  P. Bourdieu Distinction: A Social Critique of the Judgement of Taste* , 2018, Food and Culture.

[10]  T. Sowell Knowledge and Decisions , 1980 .

[11]  J. Fodor Methodological solipsism considered as a research strategy in cognitive psychology , 1980, Behavioral and Brain Sciences.

[12]  Tom M. Mitchell,et al.  Generalization as Search , 2002 .

[13]  J. Fodor The Modularity of mind. An essay on faculty psychology , 1986 .

[14]  A. Karmiloff-Smith From meta-processes to conscious access: Evidence from children's metalinguistic and repair data , 1986, Cognition.

[15]  L. Suchman Plans and situated actions , 1987 .

[16]  D. Schacter Implicit memory: History and current status. , 1987 .

[17]  P. Langley,et al.  Production system models of learning and development , 1987 .

[18]  T. Koschmann Mind over machine: The power of human intuition and expertise in the era of the computer: Hubert L. Dreyfus and Stuart E. Dreyfus (Basil Blackwell, Oxford, 1986); 223 pages, £15.00 , 1987 .

[19]  D. Broadbent,et al.  Interactive tasks and the implicit‐explicit distinction , 1988 .

[20]  Philip E. Agre,et al.  The dynamic structure of everyday life , 1988 .

[21]  P. Smolensky On the proper treatment of connectionism , 1988, Behavioral and Brain Sciences.

[22]  Geoffrey Hunter What Computers Can't Do , 1988, Philosophy.

[23]  F. Zeiss Sociobiology and epistemology , 1988 .

[24]  R. Mathews,et al.  Insight without Awareness: On the Interaction of Verbalization, Instruction and Practice in a Simulated Process Control Task , 1989 .

[25]  M. Hogg,et al.  Rediscovering the social group: A self-categorization theory. , 1989 .

[26]  Daniel B. Willingham,et al.  On the development of procedural knowledge. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[27]  J. Deneubourg,et al.  Collective patterns and decision-making , 1989 .

[28]  S. Chipman The Remembered Present: A Biological Theory of Consciousness , 1990, Journal of Cognitive Neuroscience.

[29]  Thráinn Eggertsson,et al.  Economic behavior and institutions , 1991 .

[30]  J. Bruner Acts of meaning , 1990 .

[31]  Ernest Davis,et al.  Representations of commonsense knowledge , 2014, notThenot Morgan Kaufmann series in representation and reasoning.

[32]  J. Wertsch Voices of the Mind: A Sociocultural Approach to Mediated Action , 1992 .

[33]  Thomas G. Dietterich,et al.  Readings in Machine Learning , 1991 .

[34]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[35]  Edward E. Smith,et al.  The Case for Rules in Reasoning , 1992, Cogn. Sci..

[36]  L. Cosmides,et al.  The Adapted mind : evolutionary psychology and the generation of culture , 1992 .

[37]  F. Keil Concepts, Kinds, and Cognitive Development , 1989 .

[38]  D. Laplane Thought and language. , 1992, Behavioural neurology.

[39]  A. Reber Implicit learning and tacit knowledge , 1993 .

[40]  Ryszard S. Michalski,et al.  A theory and methodology of inductive learning , 1993 .

[41]  Maja J. Matarić,et al.  Kin Recognition, Similarity, and Group Behavior , 1993 .

[42]  Robert A. Jacobs,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.

[43]  Steven P. Ketchpel Forming Coalitions in the Face of Uncertain Rewards , 1994, AAAI.

[44]  Ron Sun,et al.  Integrating rules and connectionism for robust commonsense reasoning , 1994, Sixth-generation computer technology series.

[45]  L. Schauble,et al.  Beyond Modularity: A Developmental Perspective on Cognitive Science. , 1994 .

[46]  L. Cosmides,et al.  Beyond intuition and instinct blindness: toward an evolutionarily rigorous cognitive science , 1994, Cognition.

[47]  S. Gelman,et al.  Mapping the Mind: Domain Specificity In Cognition And Culture , 1994 .

[48]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[49]  Mark Humphrys,et al.  W-learning: A simple RL-based Society of Mind , 1995 .

[50]  L. Caporael Sociality: Coordinating bodies, minds and groups. , 1995 .

[51]  Ron Sun,et al.  Robust Reasoning: Integrating Rule-Based and Similarity-Based Reasoning , 1995, Artif. Intell..

[52]  Ben J. A. Kröse,et al.  Learning from delayed rewards , 1995, Robotics Auton. Syst..

[53]  Kristian J. Hammond,et al.  The Stabilization of Environments , 1995, Artif. Intell..

[54]  Edwin Hutchins,et al.  How a Cockpit Remembers Its Speeds , 1995, Cogn. Sci..

[55]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[56]  C. Moore,et al.  Intentional relations and social understanding , 1996, Behavioral and Brain Sciences.

[57]  Ron Sun,et al.  Learning, action and consciousness: a hybrid approach toward modelling consciousness , 1997, Neural Networks.

[58]  Victor R. Lesser,et al.  Coalitions Among Computationally Bounded Agents , 1997, Artif. Intell..

[59]  C. Lebiere,et al.  The Atomic Components of Thought , 1998 .

[60]  Ron Sun,et al.  A Bottom-Up Model of Skill Learning , 1998 .

[61]  Ron Sun,et al.  Some Experiments with a Hybrid Model for Learning Sequential Decision Making , 1998, Inf. Sci..

[62]  Ron Sun,et al.  Skill Learning Using A Bottom-Up Hybrid Model , 1998 .

[63]  Ron Sun,et al.  Autonomous learning of sequential tasks: experiments and analyses , 1998, IEEE Trans. Neural Networks.

[64]  Ron Sun,et al.  Multi-agent reinforcement learning: weighting and partitioning , 1999, Neural Networks.

[65]  W. Bechtel,et al.  A companion to cognitive science , 1999 .

[66]  Ron Sun,et al.  From implicit skills to explicit knowledge: a bottom-up model of skill learning , 2001, Cogn. Sci..

[67]  I. Biederman In: An invitation to cognitive science , 2003 .