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.

• Type: Conference
• Year: 2005
• Where: DALT
• Authors: John W. Lloyd, Tim D. Sears
• Keywords: Agent Architecture, Belief Acquisition Algorithm, Belief Bases, DALT 2005