Multiagent based multisensor resource management system

Abstract

The objective of this paper is to describe the development of a distributed MultiAgent Sensory Information Fusion system which integrates data from multiple sensors such as laser radac weather radar, forward looking infrared sensors (FLIR) and associated important sensory information located in diflerent agents to accomplish requested tasks cooperatively. In this paper, we have developed a system based on the concept of ODoard Augmented Theater Surveillance (OBATS) and Internet network architecture to make the multi-agent resource management system in practice. The architecture of distributed fusion system, the coordination strategy of Global Decision Agent (GDA) and the communication between Service Agents (SAS) and GDA have been developed. Furthermore, a scenario application has been implemented to demonstrate the concept of this multi-agent system. Other potential applications have also been discussed.

Information fusion in the immune system

“…The biological immune system could provide a rich source of inspiration in the development of decentralised and distributed information fusion systems. Multiagent informa-tion fusion systems such as [13,26] are currently an active area of research. As well as the different levels of information sensed by the immune system, its overall organisation and the mechanisms of control and communication that exist could be used to develop more sophisticated multiagent information fusion systems.…”

Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks

“…Market-oriented approaches are popular in this context [Dash et al, 2007, Mullen et al, 2006, Ostwald et al, 2005. Alternatively, the agents may also be modeled to display cooperative behavior [Talukdar et al, 1998, Bowyer and Bogner, 1999, Hager and Durrant-Whyte, 1986, Luo et al, 1998]. Sensor assignment can also be modeled using a bipartite matching problem, where two node sets (the sensors and the tasks) need to be matched with largest possible weight under some constraint on the multiple usage of nodes [Kwok et al, 2002].…”