Article ID Journal Published Year Pages File Type
388099 Expert Systems with Applications 2010 13 Pages PDF
Abstract

In many settings, fully automated reasoning about tasks and resources is crucial. This is particularly important in multi-agent systems where tasks are monitored, managed and performed by intelligent agents. For these agents, it is critical to autonomously reason about the types of resources a task may require. However, determining appropriate resource types requires extensive expertise and domain knowledge. In this paper, we propose a means to automate the selection of resource types that are required to fulfil tasks. Our approach combines ontological reasoning and Logic Programming in a novel way for flexible matchmaking of resources to tasks. Using the proposed approach, intelligent agents can autonomously reason about the resources and tasks in various real-life settings and we demonstrate this here through case-studies. Our evaluation shows that the proposed approach equips intelligent agents with flexible reasoning support for task resourcing.

► Ontological reasoning and Logic Programming are combined for flexible task resourcing. ► The proposed mechanisms enable software agents to autonomously reason about the resources and tasks. ► Through case-studies, usefulness of the approach is demonstrated in various real-life settings.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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