Abstract
The ability to form coalitions of agents is central to multiagent problem-solving. However, most multi-agent systems research still takes the view that teams are simply provided - an invalid assumption in most real-world situations. This paper describes an approach to forming coalitions of agents in robotic soccer, a domain where the dynamic nature of the environment plays a key role. We describe how agents that can learn about the abilities of others can form a coalition of the better-playing agents on the team, and show that this can be used to improve the performance of a team consisting of agents with varying skill levels. We also show that this mechanism is a useful one in a setting where agents are learning to play soccer, in order to form a coalition of agents from which to learn.
Original language | English |
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Pages | 1-10 |
Number of pages | 10 |
Publication status | Published - 2004 |
Externally published | Yes |
Event | 19th National Conference on Artificial Intelligence - San Jose, CA, United States Duration: 2004 Jul 25 → 2004 Jul 26 |
Other
Other | 19th National Conference on Artificial Intelligence |
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Country/Territory | United States |
City | San Jose, CA |
Period | 2004/07/25 → 2004/07/26 |
ASJC Scopus subject areas
- General Engineering