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ATAL
2008
Springer

Controlling deliberation in a Markov decision process-based agent

8 years 5 months ago
Controlling deliberation in a Markov decision process-based agent
Meta-level control manages the allocation of limited resources to deliberative actions. This paper discusses efforts in adding meta-level control capabilities to a Markov Decision Process (MDP)-based scheduling agent. The agent's reasoning process involves continuous partial unrolling of the MDP state space and periodic reprioritization of the states to be expanded. The meta-level controller makes situation-specific decisions on when the agent should stop unrolling in order to derive a partial policy while bounding the costs of state reprioritization. The described approach uses performance profiling combined with multi-level strategies in its decision making. We present results showing the performance advantage of dynamic meta-level control for this complex agent. Categories and Subject Descriptors I.2.8 [Artificial Intelligence]: Problem Solving, Control Methods, and Search General Terms Algorithms, Performance Keywords bounded rationality, Markov decision process, meta-level c...
George Alexander, Anita Raja, David J. Musliner
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors George Alexander, Anita Raja, David J. Musliner
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