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- W2000454583 abstract "Multi-agent collaboration or teamwork and learning are two critical research challenges in a large number of multi-agent applications. These research challenges are highlighted in RoboCup, an international project focused on robotic and synthetic soccer as a common testbed for research in multi-agent systems. This article describes our approach to address these challenges, based on a team of soccer-playing agents built for the simulation league of RoboCup—the most popular of the RoboCup leagues so far. To address the challenge of teamwork, we investigate a novel approach based on the (re)use of a domain-independent, explicit model of teamwork, an explicitly represented hierarchy of team plans and goals, and a team organization hierarchy based on roles and role-relationships. This general approach to teamwork, shown to be applicable in other domains beyond RoboCup, both reduces development time and improves teamwork flexibility. We also demonstrate the application of off-line and on-line learning to improve and specialize agents' individual skills in RoboCup. These capabilities enabled our soccer-playing team, ISIS, to successfully participate in the first international RoboCup soccer tournament (RoboCup'97) held in Nagoya, Japan, in August 1997. ISIS won the third-place prize in over 30 teams that participated in the simulation league." @default.
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- W2000454583 date "1999-06-01" @default.
- W2000454583 modified "2023-10-16" @default.
- W2000454583 title "Building agent teams using an explicit teamwork model and learning" @default.
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- W2000454583 doi "https://doi.org/10.1016/s0004-3702(99)00022-3" @default.
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