Distributed constraint optimization for teams of mobile sensing agents

Abstract: Coordinating a mobile sensor team (MST) to cover targets is a challenging problem in many multiagent applications. Such applications are inherently dynamic due to changes in the environment, technology failures, and incomplete knowledge of the agents. Agents must adaptively respond by changing their locations to continually optimize the coverage of targets. We propose DCOP MST, a new model for representing MST problems that is based on Distributed Constraint Optimization Problems (DCOP). In DCOP MST, agents maintain variables for their physical positions, while each target is represented by a constraint that reflects the quality of coverage of that target. In contrast to conventional, static DCOPs, DCOP MST not only permits dynamism but exploits it by restricting variable domains to nearby locations; consequently, variable domains and constraints change as the agents move through the environment. DCOP MST confers three major advantages. It directly represents the multiple fo...

• Type: Journal
• Year: 2015
• Where: AAMAS
• Authors: Roie Zivan, Harel Yedidsion, Steven Okamoto, Robin Glinton, Katia P. Sycara
• Keywords: AAMAS 2015, Intelligent Agents