| Autor: |
Carbonell, Jaime G., Siekmann, Jörg, Gorodetsky, Vladimir, Zhang, Chengqi, Skormin, Victor A., Cao, Longbing, Stankevich, Lev, Trotsky, Denis |
| Zdroj: |
Autonomous Intelligent Systems: Multi-Agents & Data Mining; 2007, p242-255, 14p |
| Abstrakt: |
This paper describes a possibility of applying on-line learning techniques to train agents for teamwork. Special modules proposed based on immunological networks capable of on-line learning in dynamically changing environments. The above modules provide adaptive agents' behavior for teamwork after they are trained to select of primitive behaviors under variable environmental conditions. Reinforcement learning is considered to be the main method for training agents during a game. The special agent capable of on-line training for basketball competitions in RoboFIBA virtual system was developed and investigated. Examples of immunological networks for agent teamwork implementation are considered, and results of experiment with hard and training agents are described. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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