协商行为人的元层次推理

Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004). Pub Date : 2004-09-20 DOI:10.1109/IAT.2004.1342936

A. Raja, V. Lesser

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引用次数: 24

摘要

在开放环境中工作的协商代理必须对领域活动的调度和协调做出复杂的实时决策。这些决定是在资源有限和活动结果不确定的情况下作出的。我们描述了一种基于强化学习的高效元级推理方法。实证结果显示了元级推理在复杂领域中的有效性。

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Meta-level reasoning in deliberative agents

Deliberative agents operating in open environments must make complex real-time decisions on scheduling and coordination of domain activities. These decisions are made in the context of limited resources and uncertainty about the outcomes of activities. We describe a reinforcement learning based approach for efficient meta-level reasoning. Empirical results showing the effectiveness of meta-level reasoning in a complex domain are provided.

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Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).

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