Width and Complexity of Belief Tracking in Non-Deterministic Conformant and Contingent Planning
Blai Bonet, Héctor Geffner
Abstract
It has been shown recently that the complexity of belief tracking in deterministic conformant and contingent planning is exponential in a width parameter that is often bounded and small. In this work, we introduce a new width notion that applies to non-deterministic conformant and contingent problems as well. We also develop a belief tracking algorithm for non-deterministic problems that is exponential in the problem width, analyze the width of non-deterministic benchmarks, compare the new notion to the previous one over deterministic problems, and present experimental results.
Topics & Concepts
Bounded functionExponential functionExponential growthTracking (education)Mathematical optimizationMathematicsComputer scienceAlgorithmPsychologyMathematical analysisPedagogyAI-based Problem Solving and PlanningMachine Learning and AlgorithmsBayesian Modeling and Causal Inference