Automated resource-driven mission phasing techniques for constrained agents

A constrained agent is limited in the actions that it can take at any given time, and a challenging problem is to design policies for such agents to do the best they can despite their limitations. One way of improving agent performance is to break larger tasks into phases, where the constrained agent is better able to handle each phase and can reconfigure its limited capabilities differently for each phase. In this paper, we present algorithms for automating the process of finding and using mission phases for constrained agents. We analyze several variations of this problem that correspond to different classes of important constrained-agent problems, and show through analysis and experiments that our techniques can increase an agent’s rewards for varying levels of constraints on the agent and on the phases. Categories and Subject Descriptors I.2 [Computing Methodologies]: ARTIFICIAL INTELLIGENCE; I.2.8 [ARTIFICIAL INTELLIGENCE]: Control Methods, and Search General Terms ALGORITH...

• Type: Conference
• Year: 2005
• Where: ATAL
• Authors: Jianhui Wu, Edmund H. Durfee
• Keywords: Artificial Intelligence, ATAL 2005, Constrained Agents, Improving Agent, Intelligent Agents