TY - GEN
T1 - A bio-inspired multi-agent control framework
AU - Lau, H. Y.K.
AU - Wong, V. W.K.
AU - Ko, A. W.Y.
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Intelligent control
KW - Multi agent system
UR - http://www.scopus.com/inward/record.url?scp=79960717024&partnerID=8YFLogxK
U2 - 10.3182/20050703-6-CZ-1902.01078
DO - 10.3182/20050703-6-CZ-1902.01078
M3 - Conference paper (refereed)
AN - SCOPUS:79960717024
SN - 008045108X
SN - 9780080451084
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 1
EP - 6
BT - Proceedings of the 16th IFAC World Congress, IFAC 2005
PB - IFAC Secretariat
ER -