An Architecture for Rational Agents

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An Architecture for Rational Agents
Abstract. This paper is concerned with designing architectures for rational agents. In the proposed architecture, agents have belief bases that are theories in a multi-modal, higher-order logic. Belief bases can be modified by a belief acquisition algorithm that includes both symbolic, on-line learning and conventional knowledge base update as special cases. A method of partitioning the state space of the agent in two different ways leads to a Bayesian network and associated influence diagram for selecting actions. The resulting agent architecture exhibits a tight integration between logic, probability, and learning. Two illustrations of the agent architecture are provided, including a user agent that is able to personalise its behaviour according to the user’s interests and preferences.
John W. Lloyd, Tim D. Sears
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where DALT
Authors John W. Lloyd, Tim D. Sears
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