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Argumentation in Multi-Agent Systems: Third International Workshop, ArgMAS 2006, Hakodate, Japan, May 8, 2006, Revised Selected and Invited Papers

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Argumentation provides tools for designing, implementing and analyzing sophisticated forms of interaction among rational agents. It has made a solid contribution to the practice of multiagent dialogues. Application domains include: legal disputes, business negotiation, labor disputes, team formation, scientific inquiry, deliberative democracy, ontology reconciliation, risk analysis, scheduling, and logistics.

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Argumentation in Multi-Agent Systems held in Hakodate, Japan, in May 2006 as an associated event of AAMAS 2006, the main international conference on autonomous agents and multi-agent systems.

The volume opens with an original state-of-the-art survey paper presenting the current research and offering a comprehensive and up-to-date overview of this rapidly evolving area. The 11 revised articles that follow were carefully reviewed and selected from the most significant workshop contributions, augmented with papers from the AAMAS 2006 main conference, as well as from ECAI 2006, the biennial European Conference on Artificial Intelligence.

Author(s): Nicolas Maudet, Simon Parsons, Iyad Rahwan
Series: Lecture Notes in Artificial Intelligence 4766
Edition: 1
Publisher: Springer
Year: 2007

Language: English
Pages: 221

Front matter......Page 1
Introduction......Page 11
What Is Argumentation Good for?......Page 12
Argumentation for Belief Revision......Page 13
Argumentation for Deliberation and Means-Ends Reasoning......Page 14
Argumentation for Agent Communication......Page 15
Efficiency of Argumentation......Page 16
Flexibility of Communication......Page 17
Integration of Argumentation and Reasoning......Page 18
Properties of Protocols......Page 20
Concluding Remarks......Page 21
Introduction......Page 27
Overview of EALP......Page 28
Interpretation......Page 29
Overview of LMA......Page 30
Attack Relation......Page 31
Learning by Argumentation......Page 33
Knowledge Acquisition Induced by the Undercut of Assumptions......Page 34
Knowledge Acquisition Induced by Difference of Recognition......Page 36
Knowledge Acquisition Induced by Rebut......Page 38
Illustrative Examples of ABL......Page 40
Related Work......Page 42
Concluding Remarks and Future Work......Page 43
Introduction......Page 46
Justified Predictions......Page 48
Argumentation in Multiagent Learning......Page 49
Case Based Preference Relation......Page 51
Generation of Counterarguments......Page 52
Protocol Performatives......Page 55
Case Based Argumentation Protocol......Page 56
Exemplification......Page 57
Experimental Evaluation......Page 58
Related Work......Page 60
Conclusions and Future Work......Page 61
Introduction......Page 64
Dung's Framework......Page 66
Argumentation with Attacking Sets of Arguments......Page 69
Related Work......Page 78
Conclusions......Page 80
Introduction......Page 84
Preliminaries......Page 85
Argumentation Frameworks......Page 86
Arguing over Beliefs......Page 87
Arguing over Desires......Page 89
Arguing over Plans......Page 94
Related Works......Page 98
Conclusions......Page 99
Introduction......Page 101
Modelling Arguments......Page 104
Constraint Model......Page 105
Argument Model......Page 106
Solving with Arguments......Page 107
Results......Page 110
Performance......Page 113
Conclusion......Page 115
Introduction......Page 117
Social Influence Schema......Page 119
Social Arguments......Page 122
Language and Protocol......Page 123
Decision Making Functionality......Page 124
The Scenario......Page 125
Modelling Social Influences......Page 126
Agent Interaction......Page 127
Managing Social Influences......Page 129
Demanding Compensation......Page 130
Questioning Non-performance......Page 133
Related Work......Page 134
Conclusions and Future Work......Page 135
Introduction......Page 138
Agents' Mental States......Page 140
The Logical Language......Page 141
The Abstract Argumentation-Based Decision Model......Page 142
The Strategic Decision Model......Page 143
The Functional Decision Model......Page 145
Computing the Next Move in a Dialogue......Page 146
Illustrative Example......Page 147
Conclusion......Page 149
Introduction......Page 152
Agent Communication Approach......Page 153
Strategic Reasoning......Page 156
Tactic Reasoning......Page 158
Arguments Selection Mechanism......Page 159
Example......Page 163
Complexity Analysis......Page 164
Related Work and Conclusion......Page 167
Introduction......Page 171
Background and Related Research......Page 172
The Argumentation Framework......Page 174
The Dialogue Game......Page 176
The Heuristics......Page 177
Example......Page 179
Discussion......Page 180
Conclusions......Page 182
Introduction......Page 185
Repeated Negotiation Games......Page 187
Applying Persuasive Negotiation......Page 188
Reward Generation......Page 189
Step 2: Determine Rewards......Page 190
Step 3: Sending Offers and Rewards......Page 192
Evaluating Offers and Rewards......Page 193
The Reward Based Tactic......Page 194
Experimental Settings......Page 197
Empirical Results......Page 199
Conclusions......Page 201
Introduction......Page 203
Formal Characterization of Cognitive Coherence......Page 204
Local Search Algorithm......Page 206
Cognitive Coherence Applied to Agent Communication......Page 208
Argument Generation......Page 210
Issues in Argument Evaluation and Integration......Page 213
Argument Integration......Page 215
Coverage of the Presented Approach......Page 216
Conclusion......Page 218
Back matter......Page 221