The RoboCup agent behavior modeling challenge

Proceedings of: XI Workshop of Physical Agents 2010 in the framework of the Congreso Español De Informática, CEDI 2010. Valencia, Spain. 9th - 10th September, 2010.RoboCup is an international joint project that aims to foster Arti cial Intelligence (AI) and intelligent robotics research by providing a standard problem. RoboCup offers different challenges for intelligent agent researchers in a dynamic, real-time and multi-agent domain. One of these challenges, especially in the Simulation League, is the opponent modeling, which is crucial for the ultimate goal of the RoboCup project: develop a team of fully autonomous. In order to emphasize opponent-modeling approaches, the RoboCup Coach Competition was created and it was held every year (with some changes) from 2001 to 2006. Although there were several interesting research works about the agent modeling challenge during that time, several considerations were not well de ned and the competition was suspended after RoboCup Coach Competition 2006. In this paper, we propose a new approach for the competition to face the opponent modeling challenge in the RoboCup competition.No publicad

The winning advantage: using opponent models in robot Soccer

Proceeding of: Intelligent Data Engineering and Automated Learning, IDEAL 2009, 10th International Conference, Burgos, Spain, September, 23-26th, 2009.Opponent modeling is a skill in multi-agent systems (MAS) which attempts to create a model of the behavior of the opponent. This model can be used to predict the future actions of the opponent and generate appropriate strategies to play against it. Several researches present different methods to create an opponent model in the RoboCup environment. However, how these models can impact the performance of teams is an essential aspect. This paper introduces a novel approach to use efficiently opponent models in order to improve our own team behavior. The basis of this approach is the research done by CAOS Coach Team for modeling and recognizing behaviors evaluated in the RoboCup Coach Competition 2006. For using these models, it is necessary a special agent (coach) which can model the observed opponent team (based on the previous research) and communicate a counter-strategy to the coached players (using the approach proposed in this paper). The evaluation of this approach is a hard problem, but we have conducted several experiments that can help us to know if we are going in a promising direction.This work has been supported by the Spanish Government under project TRA2007-67374-C02-02.Publicad

Caos Online Coach 2006 Team Description

This paper describes the main features of the Caos Coach 2006 Simulation Team. This Coach focuses on the challenge of the opponent modelling using sequential events of the players, from observations of their main features. Also, it is able to translate observations of a dynamic and complex environment into a time-serie of recognized events. Finally, our coach implements a mechanism to compare different time-series.No publicad

Verifying RoboCup Teams

Pocreeding of: 5th International Workshop on Model Checking and Artificial Intelligence. MOCHART-2008, Patras, Greece, july, 21st, 2008.Verification of multi-agent systems is a challenging task due to their dynamic nature, and the complex interactions between agents. An example of such a system is the RoboCup Soccer Simulator, where two teams of eleven independent agents play a game of football against each other. In the present article we attempt to verify a number of properties of RoboCup football teams, using a methodology involving testing. To accomplish such testing in an efficient manner we use the McErlang model checker, as it affords precise control of the scheduling of the agents, and provides convenient access to the internal states and actions of the agents of the football teams.This work has been partially supported by the FP7-ICT-2007-1 project ProTest (215868), a Ramón y Cajal grant from the Spanish Ministerio de Educación y Ciencia, and the Spanish national projects TRA2007-67374-C02-02, TIN2006-15660-C02- 02 (DESAFIOS) and S-0505/TIC/0407 (PROMESAS).Publicad