Cognition and multi-agent interaction : from cognitive modeling to social simulation : [outgrowth of the Workshop on Cognitive Modeling of Agents and Multi-Agent Interaction, chaired by Ron Sun, held in Acapulco, Mexico, in the summer of 2003

This book explores the intersection between cognitive sciences and social sciences. In particular, it explores the intersection between individual cognitive modeling and modeling of multi-agent interaction (social stimulation). The two contributing fields - individual cognitive modeling (especially cognitive architectures) and modeling of multi-agent interaction (including social simulation and, to some extent, multi-agent systems) - have seen phenomenal growth in recent years. However, the interaction of these two fields has not been sufficiently developed. We believe that the interaction of the two may be more significant than either alone. They bring with them enormous intellectual capitals. These intellectual capitals can be profitably leveraged in creating true synergy between the two fields, leading to more in-depth studies and better understanding of both individual cognition and sociocultural processes. It is possible that an integrative field of study in cognitive and social sciences is emerging and we are laying the foundation for it. Half-title......Page 2 Title......Page 4 Copyright......Page 5 Contents......Page 6 Contributors......Page 8 Preface......Page 12 PART 1 INTRODUCTION......Page 16 1 INTRODUCTION......Page 18 2 BACKGROUND......Page 20 3 ONE HIERARCHY AND MANY LEVELS......Page 23 4 CROSSING AND MIXING LEVELS......Page 25 5 A GOLDEN TRIANGLE......Page 27 6 A MYSTERIOUS LINK......Page 30 7 THE ROOT......Page 32 8 A BRIEF OVERVIEW......Page 35 9 SUMMARY......Page 38 References......Page 39 PART 2 OVERVIEWS OF COGNITIVE ARCHITECTURES......Page 42 1 INTRODUCTION......Page 44 2 OVERVIEW OF ACT-R......Page 45 3 INSTANCE LEARNING......Page 47 3.1 Activation in Declarative Memory......Page 48 3.2 Partial Matching in Instance Retrieval......Page 49 3.3 Example Model: Sugar Factory......Page 50 4 COMPETING STRATEGIES......Page 52 4.1 Example Model: The Building Sticks Task......Page 53 5 INDIVIDUAL DIFFERENCES......Page 55 6 PERCEPTUAL AND MOTOR PROCESSES......Page 56 6.1 An Example of Perceptual Modules in Parallel......Page 57 7 SPECIALIZATION OF TASK-INDEPENDENT COGNITIVE STRATEGIES......Page 59 8 WHICH PARADIGM FOR WHAT PROBLEM?......Page 63 9 SUMMARY......Page 65 References......Page 66 1 INTRODUCTION......Page 68 2.1 The Knowledge Level, Symbol Level, and Architecture......Page 69 2.2 Problem Space Computational Model......Page 71 2.3 Parsimony......Page 75 3.1.1 Productions and Production Memory......Page 76 3.1.3 Preferences and Preference Memory......Page 77 3.2 The Soar Decision Cycle......Page 80 3.3.1 Pattern-Directed Control......Page 82 3.3.2 Reason Maintenance......Page 83 3.3.4 Automatic Subgoaling and Task Decomposition......Page 84 3.3.5 Adaptation via Generalization of Experience......Page 85 4 SOAR AGENTS WITHIN MULTIAGENT SYSTEMS......Page 86 5 LISTENING TO THE ARCHITECTURE: COMPARING SOAR TO BDI......Page 88 6 SUMMARY......Page 90 References......Page 91 1 INTRODUCTION......Page 94 2 THE OVERALL ARCHITECTURE......Page 97 3 THE ACTION-CENTERED SUBSYSTEM......Page 99 4 THE NON-ACTION-CENTERED SUBSYSTEM......Page 103 5 THE MOTIVATIONAL SUBSYSTEM......Page 105 6 THE METACOGNITIVE SUBSYSTEM......Page 107 7 DISCUSSIONS......Page 109 References......Page 112 PART 3 MODELING AND SIMULATING COGNITIVE AND SOCIAL PROCESSES......Page 116 1 INTRODUCTION......Page 118 1.1 Maximal Versus Optimal......Page 119 1.2 Understanding Maximizing Strategies......Page 120 1.3 Experimental Psychology and Reciprocal Causation......Page 121 2 COGNITIVE ARCHITECTURES......Page 122 3 METHODOLOGY......Page 124 4 HOW DO HUMANS PLAY?......Page 125 4.2 Accounting for Human Data......Page 127 5 COMPARISON WITH OTHER ARCHITECTURES......Page 129 6 COMPARISONS WITH HUMAN DATA......Page 130 7 HOW WELL DOES ACT-R PLAY?......Page 133 8 SUMMARY......Page 135 References......Page 136 1 INTRODUCTION......Page 139 2.1 Explicit vs. Implicit Learning......Page 140 2.2 A Summary of the CLARION Model......Page 141 3 ORGANIZATIONAL DESIGN......Page 144 3.1 Task......Page 145 3.2 Previous Experimental Results......Page 146 4.1 Simulation Setup......Page 147 4.2 Results......Page 148 5 SIMULATION II: EXTENDING THE SIMULATION TEMPORALLY......Page 151 6 SIMULATION III: VARYING COGNITIVE PARAMETERS......Page 153 6.2 Results......Page 154 7 DISCUSSION......Page 160 ACKNOWLEDGMENTS......Page 162 References......Page 163 1 INTRODUCTION......Page 166 2 THE BRAHMS APPROACH FOR RELATING COGNITIVE AND SOCIAL PROCESSES......Page 168 3 SIMULATION MODEL OF MARS CREW PLANNING MEETING......Page 172 3.1 Planning Meeting Time Lapse......Page 173 3.2 Planning Meeting Model Details......Page 176 3.3 Modeling Biological Motives and Behaviors vs. Goals......Page 181 4 DISCUSSION: LESSONS ABOUT ACTIVITY MODELING......Page 183 4.1 Use of the Virtual Environment Interface......Page 184 4.2 Methodology of Constructing a Brahms Model......Page 185 4.3 How Individual Behaviors Reflect and Reinforce Group Dynamics......Page 186 4.4 Distinguishing Ways of Working Together......Page 187 4.5 Summary of Relation Between Cognitive Modeling and Social Interaction......Page 189 4.6 Relation to Newell's Social Band Framework......Page 191 4.7 Application to Failure Analysis......Page 193 5 SUMMARY......Page 195 References......Page 198 1 INTRODUCTION......Page 201 2 ACT-R......Page 202 4 SIMULATION PLATFORMS......Page 205 4.1 Unreal Tournament (UT) as a Platform for MOUT......Page 206 4.2 ActivMedia Robotics as a Platform......Page 207 4.3 Time Synchronization Details for UT and ActivMedia......Page 208 5 THE MOUT DOMAIN: REQUIREMENTS FOR INTELLIGENT AGENTS IN MILITARY OPERATIONS ON URBAN TERRAIN (MOUT) AND CLOSE QUARTER BATTLE (CQB) DOMAINS......Page 209 5.2 Sample ACT-R Models......Page 210 6.1 Extracting Cognitive Primitives in Unreal Tournament......Page 212 6.2 Sampling the Space......Page 213 6.3 Converting Sampled Points to a Line Segment Representation......Page 214 6.4 An Autonomous Mapping Agent for UT......Page 215 6.7 Algorithms for Calculating Analytic Visibility......Page 216 7 COGNITIVE REPRESENTATION OF SPACE AND PERCEPTION: EGOCENTRIC AND ALLOCENTRIC REPRESENTATIONS OF DISTANCE AND BEARING......Page 217 8.2 Higher-Order Navigational Behavior......Page 219 9 COMMUNICATION......Page 220 10 IMPLEMENTING PLANNING AND TEAMWORK IN ACT-R FOR MOUT......Page 221 10.1 Schematic Plans......Page 224 10.2 Hierarchical and Partial Planning......Page 226 11 PROCEDURALIZATION, GENERALIZATION, AND FLEXIBILITY......Page 227 12 ACTION VS. REACTION......Page 230 13 SUMMARY......Page 231 References......Page 232 1 INTRODUCTION......Page 234 1.1 Virtual Humans and "Broad" Cognitive Models......Page 235 2 COGNITIVE APPRAISAL THEORY (A REVIEW)......Page 237 3 A COMPUTATIONAL MODEL OF APPRAISAL AND COPING......Page 238 3.1 EMA Overview......Page 239 3.2.1 Construct Causal Interpretation......Page 243 3.2.4 Determine Emotional State......Page 244 3.3 Limitations and Related Work......Page 245 4 MODELING SOCIAL ATTRIBUTIONS......Page 246 4.1.1 Actions and Consequences......Page 247 4.1.2 Attribution Variables......Page 248 4.1.3 Representational Primitives......Page 249 4.1.4 Axioms......Page 250 4.2 Commonsense Inference......Page 251 4.2.1 Dialog Inference......Page 252 4.2.2 Causal Inference......Page 254 4.3 Back-Tracing Algorithm......Page 255 4.4 Illustrative Example......Page 256 4.5 Discussion......Page 259 5 EVALUATION......Page 260 References......Page 263 2 HOW PEOPLE ACT TOWARDS ARTIFICIAL SYSTEMS......Page 267 3 HOW PEOPLE INTERACT WITH ARTIFICIAL SYSTEMS......Page 268 4.3 Non-cognitive Methods......Page 272 4.4 Cognitively Inspired Methods......Page 274 5 HIDE AND SEEK......Page 275 6 PERSPECTIVE TAKING......Page 277 6.1 Perspective Taking Using Similar Processes: Polyscheme......Page 280 6.2 Perspective Taking Using Similar Representations: ACT-R......Page 283 6.2.1 Perspective-Taking Process......Page 284 6.2.3 Deciding Which Cone To Go To......Page 285 7 FUTURE DIRECTIONS IN SOCIAL PERSPECTIVE TAKING......Page 286 8 SUMMARY......Page 288 References......Page 289 1 INTRODUCTION......Page 294 2 CONTROL AND IMITATION IN HUMANOID ROBOTS......Page 295 2.1 From Biological Evidence and Neuroscience Inspirations......Page 297 2.2 Extracting Natural Structure in Human Motion......Page 299 2.3 Robot Control and Perception......Page 300 2.4 Skill Acquisition for Social Robots......Page 301 3 GENERAL BEHAVIOR-BASED CONTROL......Page 302 3.1 Behavioral Structure and Artificial Intelligence......Page 303 3.2 Representational Issues......Page 304 3.3 Behavior Composition......Page 305 3.4 Adaptation and Learning......Page 307 4 COLLECTIVE BEHAVIOR-BASED ROBOTICS......Page 308 4.1 Behavior Composition......Page 309 4.2 Learning......Page 312 4.3 Activity Modeling......Page 314 5 DISCUSSION......Page 315 6 SUMMARY......Page 316 References......Page 317 1 INTRODUCTION......Page 322 2 BEFORE MACHINETTA: STEAM IN SOAR......Page 323 3.1 Components......Page 325 3.2 TOP......Page 326 3.3 Role Allocation......Page 328 3.4 Example......Page 329 4 DOMAINS......Page 331 5 NOVEL ROLE ALLOCATION METHOD......Page 333 5.1.1 GAP......Page 334 5.2 LA-DCOP......Page 335 6 EXPERIMENTS......Page 337 7 SUMMARY......Page 340 References......Page 341 1 INTRODUCTION......Page 343 2 SPATIAL AGGREGATION AND COORDINATION......Page 346 3 COMMUNICATION......Page 354 4 CULTURE......Page 361 5 SUMMARY......Page 366 References......Page 367 1 INTRODUCTION......Page 370 2 WHAT SHOULD A PROPER COGNITIVE MODEL FOR MAS AND SOCIAL THEORY BE LIKE?......Page 372 2.1 Beyond BDI: A Layered Architecture + Emotions......Page 373 2.2 The "Intentional Stance"......Page 374 2.3 Social Motives and a New Micro-Foundation......Page 375 2.4 Social Sources for Beliefs and Goals......Page 377 2.5 "We" Concept, Mental Groupness, etc.......Page 378 2.6 "As If" Minds and the Mysterious Count-As......Page 379 3 MIND: NECESSARY BUT NOT SUFFICIENT......Page 381 3.1 Cognitive Mediators of Social Phenomena......Page 382 3.1.1 Individual Mind and Social Cooperation: "Joint Activity" and "Teamwork"......Page 383 3.1.2 Norms as Mental Objects and the Need for Their Recognition as Norms......Page 384 3.2 Mind Is Not Enough: Objective Social Structures and Emergent Forms of Cooperation......Page 385 3.2.1 Objective Social Structures......Page 386 3.3 Social Cooperation Does Not Always Need Agents' Understanding, Agreement, or Rational and Joint Planning......Page 389 4 TOWARDS A BRIDGE BETWEEN COGNITION AND EMERGENCE; INTENTION AND FUNCTIONS; AUTONOMOUS GOAL-GOVERNED AGENTS AND GOAL-ORIENTED SOCIAL SYSTEMS......Page 390 4.1 "External Goals" on Goal-Oriented Agents......Page 391 4.1.1 Goal-Oriented and Goal-Governed Systems......Page 392 4.1.3 External Goals on Goal-Governed Systems......Page 393 4.1.4 From External to Internal Goals......Page 394 4.2 Finalities as External Goals......Page 395 4.3 Autonomous Gears? The Theory of Cognitive and Motivational Autonomy......Page 396 5 MODELING EMERGENT AND UNAWARE SOCIAL ORDER (COOPERATION) AMONG INTENTIONAL AGENTS: COGNITION AND SOCIAL FUNCTIONS......Page 398 6 SUMMARY......Page 401 ACKNOWLEDGMENTS......Page 402 References......Page 403 PART 4 A SYMPOSIUM......Page 406 2 ECONOMICS IS BAD SCIENCE......Page 408 3 PARTICIPATORY VALIDATION OF AGENT-BASED MODELS......Page 411 4 COGNITIVE SCIENCE IN AGENT AND MECHANISM DESIGN......Page 413 References......Page 414 1 INTRODUCTION......Page 416 2 COLLECTIVE COGNITION AS AN EMERGENT PROPERTY......Page 417 3 THE EMERGENCE BASE: IMPLICATIONS FOR INDIVIDUAL COGNITIVE MODELLING......Page 418 4 THE EMERGENCE MECHANISM: MULTI-AGENT SOCIAL INTERACTION......Page 419 5 HOLISM AND NOVELTY......Page 420 6 IRREDUCIBILITY AND DOWNWARD CAUSATION......Page 421 References......Page 422 1 INTRODUCTION......Page 424 2 THE PRINCIPLE OF ACTION DETERMINATION: A TYPE OF JUDGMENT......Page 426 3 SUMMARY......Page 429 References......Page 430 1 INTRODUCTION......Page 432 3 VARIABILITY IN EXISTING COGNITIVE ARCHITECTURES......Page 433 3.2 Other Cognitive Architectures......Page 434 4.1.2 Perception......Page 435 4.1.4 Physiology......Page 436 4.2.2 Internal Moderators......Page 437 5.1 The Development of COJACK......Page 438 ACKNOWLEDGMENTS......Page 440 References......Page 441 19 When Does Social Simulation Need Cognitive Models?......Page 443 References......Page 447 Index......Page 448 This Book Explores The Intersection Between Cognitive Sciences And Social Sciences. In Particular, It Explores The Intersection Between Individual Cognitive Modeling And Modeling Of Multi-agent Interaction. The Two Contributing Fields-individual Cognitive Modeling (especially Cognitive Architectures) And Modeling Of Multiagent Interaction (including Social Simulation And, To Some Extent, Multi-agent Systems) - Have Seen Phenomenal Growth In Recent Years. However, The Interaction Of These Two Fields Has Not Been Sufficiently Developed. The Interaction Of The Two May Be More Significant Than Either Alone. They Bring With Them Enormous Intellectual Capitals. These Intellectual Capitals Can Be Profitably Leveraged In Creating True Synergy Between The Two Fields, Leading To Better Understanding Of Both Individual Cognition And Sociocultural Processes. It Is Possible That An Integrative Field Of Study In Cognitive And Social Sciences In Emerging And We Are Laying The Foundation For It.--jacket. Prolegomena To Integrating Cognitive Modeling And Social Simulation / Ron Sun -- Modeling Paradigms In Act-r / Niel Taatgen, Christian Lebiere, And John Anderson -- Considering Soar As An Agent Architecture / Robert Wray And Randy Jones -- The Clarion Cognitive Architecture: Extending Cognitive Modeling To Social Simulation / Ron Sun -- Cognitive Architectures, Game Playing, And Human Evolution / Robert L. West, Christian Lebiere, Dan J. Bothell -- Simulating A Simple Case Of Organizational Decision Making / Isaac Nevah And Ron Sun -- Cognitive Modeling Of Social Behaviors / William J. Clancey, Et Al. -- Cognitive Agents Interacting In Real And Virtual Worlds / Bradley J. Best And Christian Lebiere -- Modeling Social Emotions And Social Attributions / Jonathan Gratch, Et Al. -- Communicating And Collaborating With Robotic Agents / J. Gregory Trafton, Et Al. -- Behavior-based Methods For Modeling And Structuring Control Of Social Robots / Dylan A. Shell And Maja J. Matarić -- Evolution Of A Teamwork Model / Nathan Schurr, Et Al. -- Sociality In Embodied Neural Agents / Domenico Parisi And Stefano Nolfi -- Cognitive Architecture And Contents For Social Structures And Interactions / Cristiano Castelfranchi -- Cognitive Science And Good Social Science / Scott Moss -- Collective Cognition And Emergence In Multi-agent Systems / Pietro Panzarasa And Nicholas R. Jennings -- Social Judgement In Multi-agent Systems / Tom R. Burns And Ewa Roszkowska -- Including Human Variability In A Cognitive Architecture To Improve Team Simulation / Frank E. Ritter And Emma Norling -- When Does Social Simulation Need Cognitive Models? / Nigel Gilbert. Edited By Ron Sun. Includes Bibliographical References And Index.