On being a teammate: experiences acquired in the design of RoboCup teams
Proceedings of the third annual conference on Autonomous Agents
Two Fielded Teams and Two Experts: A RoboCup Challenge Response from the Trenches
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
AT Humboldt - Development, Practice and Theory
RoboCup-97: Robot Soccer World Cup I
The CMUnited-97 Simulator Team
RoboCup-97: Robot Soccer World Cup I
Andhill-98: A RoboCup Team which Reinforces Positioning with Observation
RoboCup-98: Robot Soccer World Cup II
The Priority/Confidence Model as a Framework for Soccer Agents
RoboCup-98: Robot Soccer World Cup II
RoboCup-98: Robot Soccer World Cup II
RoboCup-98: Robot Soccer World Cup II
Ball-Receiving Skill Dependent on Centering in Soccer Simulation Games
RoboCup-98: Robot Soccer World Cup II
RoboCup-99: Robot Soccer World Cup III
Behavioral diversity in learning robot teams
Behavioral diversity in learning robot teams
The RoboCup synthetic agent challenge 97
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Interference as a tool for designing and evaluating multi-robot controllers
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Logfile Player and Analyzer for RoboCup 3D Simulation
RoboCup 2006: Robot Soccer World Cup X
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Increasingly, agent teams are used in realistic and complex multiagent environments. In such environments, dynamic and complex changes in the environment require appropriate adaptation of the teamwork (collaboration) among team-members. As RoboCup proposes to provide multi-agent researchers with a standard test-bed for evaluation of methodologies, it is only natural to use it for investigating this essential capability. During the RoboCup-98 workshop and competition a unique event took place: a comparative evaluation of the teamwork adaptation capabilities of 13 of the top competing teams. An evaluation attempt of this scale is a novel undertaking, and presents many novel challenges to researchers in the multi-agent community. This preliminary report describes the data-collection session, the experimental protocol, and some of the preliminary results from analysis of the data. Rather than proposing solutions and well understood results, it seeks to highlight key challenges in evaluation of multi-agent research in general, and of teamwork in particular.