Dynamic Programming and Optimal Control 3rd Edition, …

Dynamic Programming and Optimal Control3rd Edition, Volume IIbyDimitri P. BertsekasMassachusetts Institute of TechnologyChapter 6 Approximate Dynamic ProgrammingThis is an updated version of the research-oriented Chapter6 onApproximate Dynamic Programming . It will be periodically updated asnew research becomes available, and will replace the current Chapter 6 inthe book s next addition to editorial revisions, rearrangements, and new exercises,the chapter includes an account of new research, which is collected mostlyin Sections and Furthermore, a lot of new material has beenadded, such as an account of post-decision state simplifications ( ), regression-based TD methods (Section ), feature scaling ( ), policy oscillations (Section ), -policy iteration and explorationenhanced TD methods, aggregation methods (Section ), new Q-learningalgorithms (Section ), and Monte Carlo linear algebra (Section ).

simulated system trajectories and associated costs, and by using some form of “least squares fit.” Implicit in the rationale of methods based on cost function approxi-mation is of course the hypothesis that a more accurate cost-to-go approx-imation will yield a better one-step or multistep lookahead policy. This

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