Language Design Issues for Agents based on Linear Logic (Extended 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. One way to bridge this gap is to re-cast the foundations of such systems into a logic programming framework. In particular, the integration of backward- and forward-chaining techniques for linear logic provides a natural starting point for this investigation. In this paper we 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

Language Design Issues for Agents based on Linear Logic (Extended 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. One way to bridge this gap is to re-cast the foundations of such systems into a logic programming framework. In particular, the integration of backward- and forward-chaining techniques for linear logic provides a natural starting point for this investigation. In this paper we 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