RoboCup: The Robot World Cup Initiative
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Communications of the ACM
Adjustable autonomy in real-world multi-agent environments
Proceedings of the fifth international conference on Autonomous agents
Towards any-team coaching in adversarial domains
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Opponent Modeling in Multi-Agent Systems
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Defining and Using Ideal Teammate and Opponent Agent Models
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The RoboCup synthetic agent challenge 97
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Predicting opponent actions by observation
RoboCup 2004
An Efficient Behavior Classifier based on Distributions of Relevant Events
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Sequence classification using statistical pattern recognition
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
An overview on opponent modeling in RoboCup soccer simulation 2D
Robot Soccer World Cup XV
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The main goal of agent modelling is to extract and represent the knowledge about the behaviour of other agents. Nowadays, modelling an agent in multi-agent systems is increasingly becoming more complex and significant. Also, robotic soccer domain is an interesting environment where agent modelling can be used. In this paper, we present an approach to classify and compare the behaviour of a multi-agent system using a coach in the soccer simulation domain of the RoboCup.