Adaptive BDI Architecture for Multi-Agent Systems

Year 2017, Volume: 1 Issue: 2, 52 - 57, 30.06.2017

Şebnem Bora İbrahim Çakırlar

Abstract

The
increasing demand for systems that exhibits human like behavior and deals with
real world problems at runtime, is drawing attention to the development of
adaptive systems. The objective of our work is to define an adaptive
architecture for multi-agent systems, that considers BDI (Belief-Desire-Intention)
agents based on the organization theory. We define the scope of adaptation in
multi-agent systems to clarify needs for the adaptation and to define an
adaptive architecture to be able to perform the dynamic autonomous behavior at
runtime.

Keywords

Complex adaptive systems, intelligent agents, BDI architecture

References

• References [1] J. H. Holland, Complex Adaptive Systems: A Neware in Computation, MIT Press, 1992. [2] M. Morandini, L. Penserini, A. Perini and A. Susi, “Reaching goal models by evaluating system behavior”, SELMAS'05, pp.109 – 125, 2005. [3] D. Weyns, and M. Georgof, “Self-Adaptation Using Multi-Agent Systems”, IEEE Software, pp. 86-91, 2010. [4] P. Maes, Modeling Adaptive Autonomous Agents, Artificial life, 1994 [5] M. Morandini, L. Penserini, and A. Perini, “Towards goal-oriented development of self-adaptive systems”, International workshop on Software engineering for adaptive and self-managing systems, pp. 9-16. ACM, 2008. [6] S. A. DeLoach, W. Oyenan and E. T. Matson. “A capabilities based model for artificial organizations”, Journal of Autonomous Agents and Multiagent Systems, pp. 13-56, 2008. [7] George A. Polacek and Dinesh Verma, “Requirements engineering for complex adaptive systems: principles vs. rules”, 7th annual conference on systems engineering research, 2009. [8] S. Rodriguez, B. Perez-Lancho, J.F. De Paz, and J.M. Corchado, “Ovamah: Multiagent-based adaptive virtual organizations”, 2009. [9] Z. Guessom, M. Ziane and N. Faci, “Monitoring and organzational level adaptation of multi-agent systems”, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems-Volume 2, pp. 514-521, 2004. [10] D. Capera, J.-P., Gleizes, M.-P., and Glize, P., “Emergence of organisations, emergence of functions” Symposium on Adaptive Agents and Multi-Agent Systems, pp.103-108, 2003. [11] R. Razavi, J. Perrot, and N. Guelfi, Adaptive modeling: an approach and a method for implementing adaptive agents, Lecture Notes in Artificial Intelligence, pp. 136-148, 2004. [12] Z.A. Memon, and J. Treur, “A generic adaptive agent architecture integrating cognitive and affective states and their interaction”, Proceedings of the Third International Conference on Artificial General Intelligence, Atlantis Press, pp. 97-102, 2010. [13] C. Sansores and J. Pavon, “An adaptive agent model for self-organizing MAS”, Proceedings of the 7th International joint conference on Autonomous agents and multi-agent systems - Volume 3, pp. 1639-1642, 2008. [14] D. Weyns, K. Schelfthout, T. Holvoet, and O. Glorieux, “Role based model for adaptive agents” Forth Symposium on Adaptive Agents and Multiagent Systems (AISB04), pp. 75, 2006. [15] V. Dignum, and F. Dignum, “A landscape of agent systems for the real world”, Institute of Information and Computing Sciences, Utrect University, 2004. [16] S. A. DeLoach, “Multiagent systems engineering of organization-based multiagent systems”, SELMAS'05, pp.109 – 125, 2005. [17] M.Wooldridge, Reasoning about Rational Agents. The MIT Press, 2000. [18] R. L. Coser, “The Complexity of Roles as a Seedbed of Individual Autonomy”, in: The Idea of Social Structure: Papers in Honor of Robert K. Merton, 1975. [19] M. B. Riemsdijk, M. Dastani, and M. Winikoff, “Goals in agent systems: a unifying framework”, AAMAS (2) 2008: 713-720.