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An Architecture for Rational Agents Lloyd, John W. Sears, Tim D. Rational agent agent architecture belief base Bayesian networks 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik John W. Lloyd and Tim D. Sears 2006 Is Part Of Dagstuhl Seminar Proceedings, Volume 5051, Probabilistic, Logical and Relational Learning - Towards a Synthesis (2006) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.05051.3 urn:nbn:de:0030-drops-4192 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05051.3 eng https://creativecommons.org/licenses/by/4.0/legalcode