InhaltsangabeFour Disciplines in Learning and Optimization.- Perturbation Analysis.- Learning and Optimization with Perturbation Analysis.- Markov Decision Processes.- Sample-Path-Based Policy Iteration.- Reinforcement Learning.- Adaptive Control Problems as MDPs.- The Event-Based Optimization - A New Approach.- Event-Based Optimization of Markov Systems.- Constructing Sensitivity Formulas.

Perturbation Analysis of Queueing Systems.- Perturbation Analysis of Markov Chains.- Performance Sensitivities of Markov Processes.- Learning and Optimization with Perturbation Analysis.- Markov Decision Processes.- Ergodic Systems.- Sample-Path-Based Policy Iteration.- Reinforcement Learning.- Stochastic Approximation.- Temporal Difference Methods.- Identification and Adaptive Control.- Constructing Sensitivity Formulas.- Event-Based Optimization of Markov Systems.- Estimating Aggregated Potentials.