Layered approach to learning client behaviors in the robocup soccer server
نویسندگان
چکیده
منابع مشابه
A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server
In the past few years, Multiagent Systems (MAS) has emerged as an active subfield of Artificial Intelligence (AI). Because of the inherent complexity of MAS, there is much interest in using Machine Learning (ML) techniques to help build multiagent systems. Robotic soccer is a particularly good domain for studying MAS and Multiagent Learning. Our approach to using ML as a tool for building Socce...
متن کاملLayered Approach to Learning Client Behaviors in the Robocup Soccer Server
In the past few years, Multiagent Systems (MAS) has emerged as an active subfield of Artificial Intelligence (AI). Because of the inherent complexity of MAS, there is much interest in using Machine Learning (ML) techniques to help build multiagent systems. Robotic soccer is a particularly good domain for studying MAS and Multiagent Learning. Our approach to using ML as a tool for building Socce...
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Soccer Server is a simulator of RoboCup. Soccer Server provides an environment to confront two teams of players that are controlled by various types of systems with each other. Each system connects to the server as a client, which controls a player on the soccer eld via a computer network. Using this server, we can compare performances of multi-agent systems and multi-robot-control systems from...
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In 2D Soccer Simulation league, agents will decide based on information and data in their model. Effective decisions need to have world model information without any noise and missing data; however, there are few solutions to omit noise in world model data; so we should find efficient ways to reduce the effect of noise when making decisions. In this article we evaluate some simple solutions whe...
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ژورنال
عنوان ژورنال: Applied Artificial Intelligence
سال: 1998
ISSN: 0883-9514,1087-6545
DOI: 10.1080/088395198117811