Needles in a haystack: plan recognition in large spatial domains involving multiple agents
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
The RoboCup Synthetic Agent Challenge 97
RoboCup-97: Robot Soccer World Cup I
Automated Assistants to Aid Humans in Understanding Team Behaviors
RoboCup-99: Robot Soccer World Cup III
Automated Assistants for Analyzing Team Behaviors
Autonomous Agents and Multi-Agent Systems
Multi-agent strategic modeling in a robotic soccer domain
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Recognizing patterns of dynamic behaviors based on multiple relations in soccer robotics domain
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
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Three of the most important open research areas in multiagent cooperative systems are the construction of models related with the communication between agents, the multiple interactions and the behaviors adopted by agents during a task [5]. This work deals with the discovery of behaviors in multi-agent teams, more precisely in soccer teams. It is an extension of a previous work presented in [1]. The extension is focused on the discovery of tactical plays adopted by soccer-agents during a match within the context of formations. Due to the nature of team work in soccer-agent domains, the discovery of tactical behaviors should be done within the context of team formations. Nevertheless, the dynamic nature and the multiple interactions between players at each instant of the game difficult the tracking of formations, which at the same time difficult the discovery of tactical plays. In this work is proposed an original and efficient way of discovering tactical plays supported by a robust tracking of formations, even though they are submitted to dynamic changes of the world, based on the construction of topological structures. Successful results, derived from the analysis of an important number of matches of the RoboCup Simulation league matches, valid the efficiency of the model presented in this work.