Quantifying the progress of goals in intelligent agents Online publication date: Wed, 04-May-2022
by James Harland; John Thangarajah; Neil Yorke-Smith
International Journal of Agent-Oriented Software Engineering (IJAOSE), Vol. 7, No. 2, 2022
Abstract: Deliberation over goals is a fundamental feature of intelligent agent systems. In this article we provide pragmatic but principled mechanisms for quantifying the level of completeness of goals in a belief-desire-intention (BDI) agent. Our approach leverages previous work on resource and effects summarisation which we extend by accommodating both dynamic resource summaries and goal effects, while also allowing a non-binary quantification of goal completeness. We treat both goals of accomplishment (achievement goals) and goals of monitoring (maintenance goals). We reconcile such practical computation of progress estimates of goals of both types with an earlier theoretical perspective on BDI goal completeness, and thus extend the theoretical framework to include maintenance goals. Our computational mechanisms have been implemented in the abstract agent language CAN. We also provide a detailed example in an autonomous rover domain.
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