The Influence of Social Dependencies on Decision-Making: Initial Investigations with a New Game
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
A novel method for automatic strategy acquisition in N-player non-zero-sum games
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Modeling how humans reason about others with partial information
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Auction Analysis by Normal Form Game Approximation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Modeling reciprocal behavior in human bilateral negotiation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Modeling User Perception of Interaction Opportunities for Effective Teamwork
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Evolutionary stability of behavioural types in the continuous double auction
TADA/AMEC'06 Proceedings of the 2006 AAMAS workshop and TADA/AMEC 2006 conference on Agent-mediated electronic commerce: automated negotiation and strategy design for electronic markets
Agent decision-making in open mixed networks
Artificial Intelligence
Auctions, evolution, and multi-agent learning
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
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This paper presents a novel method to describe and analyze strategic interactions in settings that include multiple actors, many possible actions and relationships among goals, tasks and resources. It shows how to reduce these large interactions to a set of bilateral normal-form games in which the strategy space is significantly smaller than the original setting, while still preserving many of its strategic characteristics. We demonstrate this technique on the Colored Trails (CT) framework, which encompasses a broad family of games defining multi-agent interactions and has been used in many past studies. We define a set of representative heuristics in a three-player CT setting. Choosing players' strategies from this set, the original CT setting is analytically decomposed into canonical bilateral social dilemmas, i.e., Prisoners' Dilemma, Stag Hunt and Ultimatum games. We present a set of criteria for generating strategically interesting CT games and empirically show that they indeed decompose into bilateral social dilemmas if players play according to the heuristics. Our results have significance for multi-agent systems researchers in mapping large multi-player task settings to well-known bilateral normal-form games in a way that facilitates the analysis of the original setting.