Learning to Focus Reasoning in a Reactive Agent
نویسندگان
چکیده
In this paper we present an online learning algorithm that lets an agent architecture acquire an attentional strategy that is adapted to the environment. This allows the agent to focus its reasoning on the most rewarding parts of its knowledge base and hence achieve a higher performance under time and computational resource constraints. We use the ICARUS agent architecture as an underlying framework and we present experimental results.
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