Simulating UAV Surveillance for Analyzing Impact of Commitments in Multi-Agent Systems

Autonomous agents, by definition, have the freedom to make their own decisions. Rational agents execute actions that are in their “best interests” according to their desires. Action selection is complicated due to uncertainty when operating in a dynamic environment or where other agents can also influence the environment. This paper presents an action selection framework and algorithms that are rational with respect to multiple desires and responsive to changing desires. Coordination is layered on top of this framework by describing and analyzing how commitments affect the agents’ desires in their action selection models. Commitments may have a positive or a negative effect on an agent’s ability to satisfy its desires. This research uses simulation in the domain of UAV surveillance to experimentally explore the balance between under-commitment and over-commitment. DOI: 10.4018/jats.2012010101 2 International Journal of Agent Technologies and Systems, 4(1), 1-16, January-March 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. There has been much work on studying the semantics of commitment (Jennings, 1993). The objective of this research is to analyze the pragmatics of commitment in agent action and multi-agent coordination for the purposes of furthering our understanding of how to design and program coordinating agents. The approach taken is to explicitly model and reason about agent desires, specifically calculating the change in expected utility due to commitments. Commitments may have a negative impact on an agent’s ability to satisfy its desires. An accurate valuation of commitment is needed to determine if it is rational for an agent to commit to a goal or not. The domain of Unmanned Aerial Vehicle (UAV) surveillance is used as the representative domain for a class of problems addressed in this research. Simulation of this UAV domain is used to experimentally test this research.