{"product_id":"handbook-of-learning-and-approximate-dynamic-programming-2-ieee-press-series-on-computational-intelligence-9780471660545","title":"Handbook of Learning and Approximate Dynamic","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eADP or Approximate Dynamic Programming has gone by many different names including: reinforcement learning (RL), adaptive critics (AC), and neuro-dynamic programming (NDP). The dynamic programming approach to decision and control problems involving nonlinear dynamic systems provides the optimal solution in any stochastic or uncertain environment.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"…highly recommended to researchers, graduate students, engineers, and scientists…\" (\u003ci\u003eE-STREAMS\u003c\/i\u003e, February 2006)  \u003cp\u003e\"Clearly, this book is useful for researchers who do or want to do research on ADP.\" (\u003ci\u003eIIE Transactions-Quality \u0026amp; Reliability Engineering\u003c\/i\u003e, February 2006)\u003c\/p\u003e \u003cp\u003e\"…I would like to congratulate the editors, for putting together this wonderful collection of research contributions.\" (\u003ci\u003eComputing Reviews.com\u003c\/i\u003e, March 18, 2005)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eForeword.  \u003cp\u003e1. ADP: goals, opportunities and principles.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I: Overview.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2. Reinforcement learning and its relationship to supervised learning.\u003c\/p\u003e \u003cp\u003e3. Model-based adaptive critic designs.\u003c\/p\u003e \u003cp\u003e4. Guidance in the use of adaptive critics for control.\u003c\/p\u003e \u003cp\u003e5. Direct neural dynamic programming.\u003c\/p\u003e \u003cp\u003e6. The linear programming approach to approximate dynamic programming.\u003c\/p\u003e \u003cp\u003e7. Reinforcement learning in large, high-dimensional state spaces.\u003c\/p\u003e \u003cp\u003e8. Hierarchical decision making.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II: Technical advances.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9. Improved temporal difference methods with linear function approximation.\u003c\/p\u003e \u003cp\u003e10. Approximate dynamic programming for high-dimensional resource allocation problems.\u003c\/p\u003e \u003cp\u003e11. Hierarchical approaches to concurrency, multiagency, and partial observability.\u003c\/p\u003e \u003cp\u003e12. Learning and optimization - from a system theoretic perspective.\u003c\/p\u003e \u003cp\u003e13. Robust reinforcement learning using integral-quadratic constraints.\u003c\/p\u003e \u003cp\u003e14. Supervised actor-critic reinforcement learning.\u003c\/p\u003e \u003cp\u003e15. BPTT and DAC - a common framework for comparison.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III: Applications.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16. Near-optimal control via reinforcement learning.\u003c\/p\u003e \u003cp\u003e17. Multiobjective control problems by reinforcement learning.\u003c\/p\u003e \u003cp\u003e18. Adaptive critic based neural network for control-constrained agile missile.\u003c\/p\u003e \u003cp\u003e19. Applications of approximate dynamic programming in power systems control.\u003c\/p\u003e \u003cp\u003e20. Robust reinforcement learning for heating, ventilation, and air conditioning control of buildings.\u003c\/p\u003e \u003cp\u003e21. Helicopter flight control using direct neural dynamic programming.\u003c\/p\u003e \u003cp\u003e22. Toward dynamic stochastic optimal power flow.\u003c\/p\u003e \u003cp\u003e23. Control, optimization, security, and self-healing of benchmark power systems.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402650100055,"sku":"9780471660545","price":142.16,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471660545.jpg?v=1730481112","url":"https:\/\/bookcurl.com\/products\/handbook-of-learning-and-approximate-dynamic-programming-2-ieee-press-series-on-computational-intelligence-9780471660545","provider":"Book Curl","version":"1.0","type":"link"}