Towards alternative approaches to reasoning about goals

Patricia H Shaw, Rafael H Bordini

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

Agent-oriented programming languages have gone a long way in the level of sophistication offered to programmers, and there has also been much progress in tools to support multi-agent systems development using such languages. However, much work is still required in mechanisms that can reduce the burden, typically placed on programmers, of ensuring that agents behave rationally, hence being effective and as efficient as possible. One such mechanisms is reasoning about declarative goals, which is increasingly appearing in the agents literature; it allows agents to make better use of resources, to avoid plans hindering the execution of other plans, and to be able to take advantage of opportunities for reducing the number of plans that have to be executed to achieve certain combinations of goals. In this paper, we introduce a Petri-net based approach to such reasoning, and we report on experimental results showing that this technique can obtain comparable improvements on an agent's behaviour to other existing approaches (our experiments do not yet cover reasoning about resource usage). Our long-term goal is to provide a number of alternative approaches for such reasoning, evaluate and compare their performances under different configurations, and incorporate them into interpreters for agent-oriented programming languages in such a way that the most appropriate approach is used at given circumstances.

Original languageEnglish
Title of host publicationDeclarative Agent Languages and Technologies V
Subtitle of host publication5th International Workshop, DALT 2007, Revised Selected and Invited Papers
EditorsM. Baldoni, T. C. Son, M. B. van Riemsdijk, M. Winikoff
PublisherSpringer Nature
Pages104-121
Number of pages18
ISBN (Print)3540775633, 9783540775638
DOIs
Publication statusPublished - 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4897 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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