Towards flexible teamwork in persistent teams: Extended report

被引:12
|
作者
Tambe, M
Zhang, WX
机构
[1] Univ So Calif, Inst Informat Sci, Marina Del Rey, CA 90292 USA
[2] Univ So Calif, Dept Comp Sci, Marina Del Rey, CA 90292 USA
基金
美国国家科学基金会;
关键词
multi-agent systems; teamwork; persistence; Markov decision processes;
D O I
10.1023/A:1010026728246
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Teamwork is a critical capability in multi-agent environments. Many such environments mandate that the agents and agent-teams must be persistent i.e., exist over long periods of time. Agents in such persistent teams are bound together by their long-term common interests and goals. This paper focuses on flexible teamwork in such persistent teams. Unfortunately, while previous work has investigated flexible teamwork, persistent teams remain unexplored. For flexible teamwork, one promising approach that has emerged is model-based, i.e., providing agents with general models of teamwork that explicitly specify their commitments in teamwork. Such models enable agents to autonomously reason about coordination. Unfortunately, fur persistent trams, such models may lead to coordination and communication actions that while locally optimal, are highly problematic for the team's long-term goals. We present a decision-theoretic technique based on Markov decision processes to enable persistent teams to overcome such limitations of the model-based approach. In particular, agents reason about expected ream utilities of future team states that are projected to result from actions recommended by the teamwork model, as well as lower-cost (or higher-cost) variations on these actions. To accommodate real-time constraints, this reasoning is done in an any-time fashion. Implemented examples from an analytic search tree and some real-world domains are presented.
引用
收藏
页码:159 / 183
页数:25
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