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• W2153668164 abstract "We present Variable Influence Structure Analysis, or VISA, an algorithm that performs hierarchical decomposition of factored Markov decision processes. VISA uses a dynamic Bayesian network model of actions, and constructs a causal graph that captures relationships between state variables. In tasks with sparse causal graphs VISA exploits structure by introducing activities that cause the values of state variables to change. The result is a hierarchy of activities that together represent a solution to the original task. VISA performs state abstraction for each activity by ignoring irrelevant state variables and lower-level activities. In addition, we describe an algorithm for constructing compact models of the activities introduced. State abstraction and compact activity models enable VISA to apply efficient algorithms to solve the stand-alone subtask associated with each activity. Experimental results show that the decomposition introduced by VISA can significantly accelerate construction of an optimal, or near-optimal, policy." @default.
• W2153668164 created "2016-06-24" @default.
• W2153668164 creator A5086943516 @default.
• W2153668164 creator A5089808068 @default.
• W2153668164 date "2006-12-01" @default.
• W2153668164 modified "2023-09-24" @default.
• W2153668164 title "Causal Graph Based Decomposition of Factored MDPs" @default.
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• W2153668164 hasPublicationYear "2006" @default.
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