Reasoning about intentions in uncertain domains

Paper:

Reasoning about intentions in uncertain domains

Appears:

Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty, Toulouse, 2001.

Abstract:

The design of agents that are situated in real world domains involves dealing with undertainty in terms of dynamism, observability and non-determinism. These three types of uncertainty, when combined with the real-time requirements of many application domains, imply that an agent must be capable of effectively coordinating its reasoning. As such, situated belief-desire-intention (BDI) agents need an efficient intention reconsideration policy, which defines when computational resources are better spent on either object-level reasoning or action. This paper presents an implementation of such a policy by modelling intention reconsideration as a partially observable Markov decision process (POMDP). The motivation for a POMDP implementation of intention reconsideration is that the two processes have simialr properties and functions, as we demonstrate in the paper. Our approach achieves better results than existing intention reconsideration frameworks, as is demonstrated empirically in this paper.

Keywords:

Belief/desire/intention architecture, intention reconsideration, POMDPs.

Availability:

This paper is available as a compressed Postscript file.

Other information:

The Postscript file contains the camera-ready copy that appeared in the conference proceedings.