Handbook of Simulation Optimization. - Fu, Michael C. (New York, NY : Springer, 2014)
12.2 A Brief Review of Model-Based Methods -- 12.3 A Model Reference Optimization Framework -- 12.3.1 Convergence Result -- 12.3.2 Simulation Optimization -- 12.4 A Stochastic Approximation Framework -- 12.4.1 Convergence Results -- Convergence of the CE Method -- Model-Based Annealing Random Search (MARS) -- 12.4.2 Simulation Optimization -- Application of MARS to Finite-Horizon Markov Decision Processes -- 12.5 A Stochastic Averaging Approach -- 12.6 Conclusions and Open Research Questions -- References -- 13 Solving Markov Decision Processes via Simulation -- 13.1 Introduction -- 13.2 Background -- 13.2.1 Notation and Assumptions -- 13.2.2 Performance Metrics -- 13.2.3 Bellman Equations -- 13.3 Discounted Reward MDPs -- 13.3.1 Q-Learning -- 13.3.2 Q-Learning with Function Approximation -- Basis Functions -- Bellman Error -- 13.3.3 SARSA() -- 13.3.4 Approximate Policy Iteration -- 13.3.5 Actor-Critic Algorithm -- 13.3.6 Evolutionary Policy Iteration -- 13.4 Average Reward MDPs -- 13.4.1 Relative Q-Learning -- 13.4.2 R-SMART -- SSP-Version -- Contraction-Factor Version -- 13.5 Finite Horizon MDPs -- 13.5.1 Special Case of Stochastic Shortest Path (SSP) -- 13.5.2 Pursuit Learning Automata (PLA) Sampling -- 13.6 Numerical Results -- 13.6.1 Infinite Horizon -- 13.6.2 Finite Horizon -- 13.7 Extensions -- 13.8 Convergence Theory -- 13.9 Concluding Remarks -- References -- Index.
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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Keywords: Discrete-time systems -- Handbooks, manuals, etc; Electronic books