A bio-inspired multi-agent control framework
World Congress, Volume # 16 | Part# 1
H. Y. K. Lau; V. W. K. Wong; A. W. Y. Ko
Digital Object Identifier (DOI)
artificial intelligence,intelligent control,multi agent system
The biological world has often offered inspirations to novel approaches to solving engineering problems. This paper presents an engineering analogy of the human immune system, known as the artificial immune system (AIS) for the strategic control of multi-agent based systems such as fleet of autonomous guided vehicles or a multi-jointed manipulator. The human immune system is a complex, adaptive and highly distributed system that exhibits the behaviors of autonomy, self-organizing, distributivity, fault tolerance, robustness, learning and memory, which is underpinned by a set of theories including the immune discrimination and specificity theories. A distributed control framework is developed based on the conceptual framework of the immune system. The AIS-based multi-agent control paradigm is studied via two key mechanisms in the generalized control hierarchy, namely, detection of events and the activation of control actions. Simulation and experimental study using a fleet of autonomous guided vehicles in a material handling system to illustrate the effectiveness of the proposed framework.
 Benjamini, E., Sunshine, G. and S. Leskowitz (1996). Immunology: A Short Course, Wiley-Liss, New York, USA.  Bentley, P. J. (1999). Evolution Design by Computers, Morgan Kaufmann, Bath, U.K.  de Castro, L. N. and F. J. Von Zuben (2000). The clonal selection algorithm with engineering applications, Proc. GECCO 2000, pp. 36-37.  Dasgupta, D., KrishnaKumar, K., Wong, D. and M. Berry (2004). Negative selection algorithm for aircraft fault detection, Proc. 3rd Int. Conf. Artificial Immune Systems (ICARIS 2004), pp. 1-13.  Fukuda, T., Ueyama, T. and F. Arai (1991). Control strategy for a network of cellular robotsdetermination of a master cell for cellular robotic network based on a potential energy, Proc. of IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1616-1621.  Hart, E., Ross, P., Webb. A. and A. Lawson (2003). A role of immunology in "next generation" robot controllers, Proc. 2nd Int. Conf. Artificial Immune Systems (ICRAIS 2003).  Ishiguro, A., Kondo, T., Watanabe, Y., Shirai, Y. and Y. Ichikawa (1997). Emergent construction of artificial immune network for autonomous mobile robots, Proc. System Man Cybernetics, SMC 97, pp. 1222-1228.  Ko, A., Lau, Y. K. H. and T. L. Lau (2004). An immuno control framework for decentralized mechantronic control, Proc. 3rd Int. Conf. Artificial Immune Systems (ICARIS 2004), pp. 91-105.  Lau, H. Y. K. and V. W. K. Wong (2003). Immunologic Control Framework for Automated Material Handling, Proc. 2nd Int. Conf. Artificial Immune Systems (ICRAIS 2003), pp. 57-68.  Lau, H. Y. K. and V. W. K. Wong (2004). Immunological responses manipulation of AIS agents, Proc. 3rd Int. Conf. Artificial Immune Systems (ICARIS 2004), pp. 65-79.  Lee, D. W., J. H. Jun, and K. B., Sim (1999). Realization of cooperative strategies and swarm behavior in distributed autonomous robotic systems using artificial immune system, Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Vol. 6, pp. 614-619.  Lee, D. W. and K. B. Sim (1997). Artificial Immune Network-based Cooperative Control in Collective Autonomous Mobile Robots, Proc. IEEE Int. Workshop on Robot and Human Communication, pp. 58-63.  Meshref, H. and H. VanLandingham (2000). Artificial Immune Systems: Application to Autonomous Agent, Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Vol. 1, pp. 61- 66.  Michelan, R. and F. J. Von Zuben (2002). Decentralized control system for autonomous navigation based on an evolved artificial immune network, Proc. 2002 Congress on Evolutionary Computation (CEC '0), Vol. 2, pp. 1021-1026.  Playfair, J. H. L. and B. M. Chain (2001). Immunology at a Glance, Blackwell Science, Bodmin, Cornwall.  Sipper, M. (2002). Machine Nature: the Coming Age of Bio-inspired Computing, McGraw-Hill, New York.  Wooldridge, M. J. (2002). An Introduction to multiagent systems, John Wiley & Sons, West Sussex, England.