Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Algebraic decision diagrams and their applications
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Bounded-parameter Markov decision process
Artificial Intelligence
Algebraic structure theory of sequential machines (Prentice-Hall international series in applied mathematics)
Model minimization in Markov decision processes
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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We describe an algorithm for solving MDPs with large state and action spaces, represented as factored MDPs with factored action spaces. Classical algorithms for solving MDPs are not effective since they require enumerating all the states and actions. As such, model minimization techniques have been proposed, and specifically, we extend the previous work on model minimization algorithm for MDPs with factored state and action spaces. Using algebraic decision diagrams, we compactly represent blocks of states and actions that can be regarded equivalent. We describe the model minimization algorithm that uses algebraic decision diagrams, and show that this new algorithm can handle MDPs with millions of states and actions.