# Agents via Mixed-Mode Computation in Linear Logic

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## Abstract

Agent systems based on the *Belief*, *Desire* and *Intention* model of Rao and Georgeff have been used for a number of successful applications. However, it is often difficult to learn how to apply such systems, due to the complexity of both the semantics of the system and the computational model. In addition, there is a gap between the semantics and the concepts that are presented to the programmer. In this paper we address these issues by re-casting the foundations of such systems into a logic programming framework. In particular we show how the integration of backward- and forward-chaining techniques for linear logic provides a natural starting point for this investigation. We discuss how the integrated system provides for the interaction between the proactive and reactive parts of the system, and we discuss several aspects of this interaction. In particular, one perhaps surprising outcome is that goals and plans may be thought of as *declarative* and *procedural* aspects of the same concept. We also discuss the language design issues for such a system, and particularly the way in which the potential choices for rule evaluation in a forward-chaining manner is crucial to the behaviour of the system.

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