Details
| Original language | English |
|---|---|
| Article number | A313 |
| Journal | International Journal of Advanced Robotic Systems |
| Volume | 10 |
| Publication status | Published - 20 Aug 2013 |
| Externally published | Yes |
Abstract
In this article we introduce a blackboardbased 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 logicbased 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.
Keywords
- Blackboard, Evolutionary, Fuzzy Logic, Mobile Robot, Motivations, Multi-Agent
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Computer Science Applications
- Computer Science(all)
- Artificial Intelligence
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In: International Journal of Advanced Robotic Systems, Vol. 10, A313, 20.08.2013.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Fuzzy motivations in a multiple agent behaviour-based architecture
AU - Arredondo, Tomás V.
AU - Freund, Wolfgang
AU - Navarro-Guerrero, Nicolás
AU - Castillo, Patricio
PY - 2013/8/20
Y1 - 2013/8/20
N2 - In this article we introduce a blackboardbased 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 logicbased 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.
AB - In this article we introduce a blackboardbased 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 logicbased 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.
KW - Blackboard
KW - Evolutionary
KW - Fuzzy Logic
KW - Mobile Robot
KW - Motivations
KW - Multi-Agent
UR - http://www.scopus.com/inward/record.url?scp=84883330277&partnerID=8YFLogxK
U2 - 10.5772/56578
DO - 10.5772/56578
M3 - Article
AN - SCOPUS:84883330277
VL - 10
JO - International Journal of Advanced Robotic Systems
JF - International Journal of Advanced Robotic Systems
SN - 1729-8806
M1 - A313
ER -