A simple method for decision making in robocup soccer simulation 3d environment

Abstract—In this paper new hier archical hybrid fuzzy-crisp methods for decision making and action selection of an agent in soccer simulation 3D environment are presented. First, the skills of an agent are introduced, implemented and classified in two layers, the basicskills and the highlevel skil...

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Autores:
Maleki, Khashayar Niki
Valipour, Mohammad Hadi
Ashrafi, Roohollah Yeylaghi
Mokari, Sadegh
Jamali, M. R.
Lucas, Caro
Tipo de recurso:
Article of journal
Fecha de publicación:
2008
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/24453
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/24453
http://bdigital.unal.edu.co/15490/
Palabra clave:
Multi-Agent systems
Machine learning
Artificial intelligence
Reinforcement learning
Fuzzy Logic
Fuzzy reinforcement learning
RoboCup soccer simulation.
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Abstract—In this paper new hier archical hybrid fuzzy-crisp methods for decision making and action selection of an agent in soccer simulation 3D environment are presented. First, the skills of an agent are introduced, implemented and classified in two layers, the basicskills and the highlevel skills. In the second layer, a twophase mechanism for decision making is introduced. In phase one, some useful methods are implemented which check the agent’s situation for performing required skills. In the next phase, the team str ategy, team for mation, agent’s role and the agent’s positioning system are introduced. A fuzzy logical approach is employed to recognize the team strategy and further more to tell the player the best position to move. At last, we comprised our implemented algor ithm in the Robocup Soccer Simulation 3D environment and results showed th eefficiency of the introduced methodology.