Agent autonomy through the M-3 motivational taxonomy

S. Munroe, M. Luck

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

Abstract

The concept of autonomy applied to computational agents refers to the ability of an agent to act without the direct intervention of human users in the selection and satisfaction of goals. Actual implementations of mechanisms to enable agents to display autonomy are, however, at an early stage of development and much remains to be done to fully explicate the issues involved in the development of such mechanisms. Motivation has been used by several researchers as such an enabler of autonomy in agents. In this paper we describe a motivational taxonomy, the M-3 Taxonomy, comprising domain, social and constraint motivations, which we argue is a sufficient range of motivations to enable autonomy in all the main aspects of agent activity. Underlying this taxonomy is a motivational model that describes how motivation can be used to bias an agent's activities towards that which is important in a given context, and also how motivational influence can be dynamically altered through the use of motivational cues, that are features in the environment that signify important situations to an agent.
Original languageEnglish
Title of host publicationAgents and Computational Autonomy
Subtitle of host publicationPotential, Risks, and Solutions
EditorsM Nickles, M Rovatsos, G Weiss
Place of PublicationBerlin, Geramny
PublisherSpringer
Pages55-67
Number of pages13
ISBN (Print)9783540224778
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science
Volume2969

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  • Cite this

    Munroe, S., & Luck, M. (2004). Agent autonomy through the M-3 motivational taxonomy. In M. Nickles, M. Rovatsos, & G. Weiss (Eds.), Agents and Computational Autonomy: Potential, Risks, and Solutions (pp. 55-67). (Lecture Notes in Computer Science; Vol. 2969). Springer.