RoboCup 2001: Robot Soccer World Cup V
Multi-Agent Simulation for Crisis Management
KMN '02 Proceedings of the IEEE Workshop on Knowledge Media Networking
Coalition formation through motivation and trust
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
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
Synthetic humans in emergency response drills
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Policy recognition for multi-player tactical scenarios
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Mass programmed agents for simulating human strategies in large scale systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Modeling human behavior for virtual training systems
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Modeling agents through bounded rationality theories
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Less is more: restructuring decisions to improve agent search
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Modeling agents based on aspiration adaptation theory
Autonomous Agents and Multi-Agent Systems
Evaluating the Applicability of Peer-Designed Agents in Mechanisms Evaluation
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
The effectiveness of peer-designed agents in agent-based simulations
Multiagent and Grid Systems
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In this paper we report results of an extensive evaluation of people's ability to reproduce the strategies they use in simple real-life settings. Having the ability to reliably capture people's strategies in different environments is highly desirable in Multi-Agent Systems (MAS). However, as trivial and daily as these strategies are, the process is not straightforward and people often have a different belief of how they act. We describe our experiments in this area, based on the participation of a pool of subjects in four different games with variable complexity and characteristics. The main measure used for determining the closeness between the two types of strategies used is the level of similarity between the actions taken by the participants and those taken by agents they programmed in identical world states. Our results indicate that generally people have the ability to reproduce their game strategies for the class of games we consider. However, this process should be handled carefully as some individuals tend to exhibit a behavior different from the one they program into their agents. The paper evaluates one possible method for enhancing the process of strategy reproduction.