An Architecture for Rational Agents

Authors John W. Lloyd, Tim D. Sears

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John W. Lloyd
Tim D. Sears

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John W. Lloyd and Tim D. Sears. An Architecture for Rational Agents. In Probabilistic, Logical and Relational Learning - Towards a Synthesis. Dagstuhl Seminar Proceedings, Volume 5051, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)


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. This approach to agent architecture is illustrated by a user agent that is able to personalise its behaviour according to the user's interests and preferences.
  • Rational agent
  • agent architecture
  • belief base
  • Bayesian networks


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