Abstract
Classical control systems are based on feedback techniques and models that generally cannot manage computational complexity, nonlinearity and uncertainty. Moreover, classical control cannot adapt well to the variability of the processes under control in a dynamic fashion. However, agent-based control eases combinatorial complexity by enabling a robust partitioning of knowledge and behaviors. It is a difficult challenge to create the infrastructure, development system and validation tools for agent systems. In this paper we discuss fundamental steps to achieve the foundation infrastructure for creating agents but also we address several guidelines to create the agents and the requirements to present this to non-agent specialists.
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References
Christensen, J.H.: Holonic Manufacturing Systems: Initial Architecture and Standards Directions. In: First European Conference on Holonic Manufacturing Systems, Hanover, Germany (1994)
FIPA: The Foundation for Intelligent Physical Agents, Geneva, Switzerland (1997)
Mařík, V., Pěchouček, M., Štěpánková, O.: Social knowledge in multi-agent systems. In: Luck, M., Mařík, V., Štěpánková, O., Trappl, R. (eds.) ACAI 2001 and EASSS 2001. LNCS(LNAI), vol. 2086, pp. 211–245. Springer, Heidelberg (2001)
Maturana, F.P., Staron, R., Hall, K.: Methodologies and Tools for Agents in Distributed Control. IEEE Intelligent Systems Magazine, 42–49 (January/February 2005)
Leitão, P., Restivo, F.: A Holonic Control Approach for Distributed Manufacturing. In: Marik, V., Camarinha-Matos, L.M., Afsarmanesh, H. (eds.) Knowledge and Technology Integration in Production and Services: Balancing Knowledge and Technology in Product and Service Life Cycle, pp. 263–270. Kluwer Academic Publishers, Dordrecht (2002)
Tichý, P.: Middle-agents Organized in Fault Tolerant and Fixed Scalable Structure. Computing and Informatics 22, 597–622 (2003) ISSN 1335-9150
Shen, W., Norrie, D., Barthès, J.P.: Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing. Taylor & Francis, London (2001)
Vasko, D., Maturana, F., Bowles, A., Vandenberg, S.: Autonomous Cooperative Systems Factory Control. In: PRIMA 2000, Australia (2000)
Discenzo, F., Maturana, F., Chang, D.: Managed Complexity in an Agent-Based Vent Fan Control system Based on Dynamic Reconfiguration. In: International Conference on Complex Systems, Nashua, NH, June 9-14 (2002)
Maturana, F., Balasubramanian, S., Vasko, D.: An Autonomous Cooperative System for Material Handling System Applications. In: ECAI 2000 Proceedings of the 14th European Conference on Artificial Intelligence. IOS Press, Amsterdam (2000)
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Maturana, F.P., Staron, R.J., Tichý, P., Šlechta, P., Vrba, P. (2005). A Strategy to Implement and Validate Industrial Applications of Holonic Systems. In: Mařík, V., William Brennan, R., Pěchouček, M. (eds) Holonic and Multi-Agent Systems for Manufacturing. HoloMAS 2005. Lecture Notes in Computer Science(), vol 3593. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11537847_10
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DOI: https://doi.org/10.1007/11537847_10
Publisher Name: Springer, Berlin, Heidelberg
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