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We propose a novel randomized linear programming algorithm for approximating the optimal policy of the discounted Markov decision problem.
Dynamic Programming
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Les problemes de decisions sequentielles
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Dynamic programming and optimal control
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Finite-sample convergence rates for q-learning and indirect algorithms
Michael J Kearns and Satinder P Singh · 1999
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On the complexity of policy iteration
Yishay Mansour and Satinder Singh · 1999
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The linear programming approach to approximate dynamic programming
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An efficient stochastic approximation algorithm for stochastic saddle point problems
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Arkadi Nemirovski, Anatoli Juditsky, Guanghui Lan, and Alexander Shapiro · 2009
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Abstract dynamic programming
Dimitri P Bertsekas · 2013
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Improved and generalized upper bounds on the complexity of policy iteration
Bruno Scherrer · 2013
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The value iteration algorithm is not strongly polynomial for discounted dynamic programming
Eugene A Feinberg and Jefferson Huang · 2014
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Path finding methods for linear programming: Solving linear programs in o (vrank) iterations and faster algorithms for maximum flow
Yin Tat Lee and Aaron Sidford · 2014
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Markov decision processes: discrete stochastic dynamic programming
Martin L Puterman · 2014
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Efficient inverse maintenance and faster algorithms for linear programming
Yin Tat Lee and Aaron Sidford · 2015
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