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A multi-agent environment in robotics

Published online by Cambridge University Press:  09 March 2009

Eugénio Oliveira
Affiliation:
Faculty of Engineering, Porto University, Rua dos Bragas, 4099, Porto codex Portugal
R. Camacho
Affiliation:
Faculty of Engineering, Porto University, Rua dos Bragas, 4099, Porto codex Portugal
C. Ramos
Affiliation:
Faculty of Engineering, Porto University, Rua dos Bragas, 4099, Porto codex Portugal

Summary

The use of Multi-Agent Systems as a Distributed AI paradigm for Robotics is the principal aim of our present work. In this paper we consider the needed concepts and a suitable architecture for a set of Agents in order to make it possible for them to cooperate in solving non-trivial tasks.

Agents are sets of different software modules, each one implementing a function required for cooperation. A Monitor, an Acquaintance and Self-knowledge Modules, an Agenda and an Input queue, on the top of each Intelligent System, are fundamental modules that guarantee the process of cooperation, while the overall aim is devoted to the community of cooperative Agents. These Agents, which our testbed concerns, include Vision, Planner, World Model and the Robot itself.

Type
Article
Copyright
Copyright © Cambridge University Press 1991

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References

1.Hunhs, M. (ed.), Distributed Artificial Intelligence Research Notes in Artificial Intelligence Series (Morgan Kaufmann Publishers, Los Altos, California, 1987).Google Scholar
2.Bond, A.H., Gasser, Les (eds.), Readings in Distributed Artificial Intelligence (Morgan Kaufman Publishers, Los Altos, California, 1988).Google Scholar
3.Oliveira, E., Ramos, C. & Camacho, R., AI Systems cooperation for Robotics Proceedings of First Workshop on Robotics and CIM, Lisbon section B 919 (1989).Google Scholar
4.Walhster, W. & Kobsa, A., “Dialogue-Based User ModelsProceedings IEEE 74, 948960 (07, 1986).CrossRefGoogle Scholar
5.de Kleer, J., “An assumption-based TMSArtificial Intelligence 28, 27162 (1986).CrossRefGoogle Scholar
6.Hough, P.V.C., “Method and means for recognizing complex patterns” U.S., Patent 3.069.654, (1962).Google Scholar