Fuzzy Motivations in a Multiple Agent Behaviour-Based Architecture

In this article we introduce a blackboard-based multiple agent system framework that considers biologically-based motivations as a means to develop a user friendly interface. The framework includes a population-based heuristic as well as a fuzzy logic-based inference system used toward scoring syste...

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Bibliographic Details
Published inInternational journal of advanced robotic systems Vol. 10; no. 8
Main Authors Arredondo, Tomás V., Freund, Wolfgang, Navarro-Guerrero, Nicolás, Castillo, Patricio
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 20.08.2013
Sage Publications Ltd
SAGE Publishing
Subjects
Behavior
Cognition & reasoning
Fuzzy logic
Fuzzy systems
Homing
Long term planning
Low cost
Motivation
Optimization
Robots
Mobile Robot
Motivations
Fuzzy Logic
Evolutionary
Multi-Agent
Blackboard
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Summary:In this article we introduce a blackboard-based multiple agent system framework that considers biologically-based motivations as a means to develop a user friendly interface. The framework includes a population-based heuristic as well as a fuzzy logic-based inference system used toward scoring system behaviours. The heuristic provides an optimization environment and the fuzzy scoring mechanism is used to give a fitness score to possible system outputs (i.e. solutions). This framework results in the generation of complex behaviours which respond to previously specified motivations. Our multiple agent blackboard and motivation-based framework is validated in a low cost mobile robot specifically built for this task. The robot was used in several navigation experiments and the motivation profile that was considered included “curiosity”, “homing”, “energy” and “missions”. Our results show that this motivation-based approach permits a low cost multiple agent-based autonomous mobile robot to acquire a diverse set of fit behaviours that respond well to user and performance expectations. These results also validate our multiple agent framework as an incremental, flexible and practical method for the development of robust multiple agent systems.
ISSN:1729-8806
1729-8814
DOI:10.5772/56578