In this enlarged edition of a modern classic (first published in 1991) on the battle of chess ideas, grandmaster Mihai Suba developed the concept of ?dynamic potential? in modern chess strategy. In improving your position on the board the old strategy principles often lead to conflicting conclusions. Suba takes another view on the meaning of, for example, ?bad positions? and ?quiet moves?, and uses a light touch to explain his ideas. With many entertaining and instructive examples the author explores ?the accumulation of potential? as the modern way to get the advantage. A thought-provoking and yet very practical guide.

This comprehensive reference work presents detailed bibliographical information about worldwide chess periodicals past to present. It contains 3,163 entries and many cross-references. Information for each entry includes year and country of publication, frequency, sponsors, publisher, editors, subject, language, alternate titles, mergers, continuations, and holdings in chess libraries. Includes an index of periodicals by country and a general index of periodical titles.

Chess is a game of wits that calls for strategy, tactics and intuition. The game has a long history spanning several centuries and has been played the world over for it develops strategic thinking and tactical planning skills. Chess is intellectually stimulating and challenging - and offers limitless possibilities at every stage of play. The very nature of the game makes it amenable to systematic study and mastery over time. There are several variants of Chess which offer a level-playing field for amateurs who can think logically. This book is the outcome of the author's curiosity about new Chess variants which can be played on boards with different geometries, different sets of rules with different objectives. This entirely new look at Chess offers: Chess inspired games that reflect situations and events from daily life. Games inspired by popular sports such as squash, volleyball and cricket. Chess games as a motivational tool in education to help students develop interest and liking for their subjects and achieve better academic performance. Chess inspired puzzles. Chess as an outdoor sport and indoor team-game. A. V. Murali's engrossing book highlights the different perspectives of Chess - showcasing its broader applicability, not just for amusement, but for physical and intellectual development as well.

Volumes for 1898-1968 include a directory of publishers.

This is the leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization. The treatment focuses on basic unifying themes, and conceptual foundations. It illustrates the versatility, power, and generality of the method with many examples and applications from engineering, operations research, and other fields. It also addresses extensively the practical application of the methodology, possibly through the use of approximations, and provides an extensive treatment of the far-reaching methodology of Neuro-Dynamic Programming/Reinforcement Learning. Among its special features, the book 1) provides a unifying framework for sequential decision making, 2) treats simultaneously deterministic and stochastic control problems popular in modern control theory and Markovian decision popular in operations research, 3) develops the theory of deterministic optimal control problems including the Pontryagin Minimum Principle, 4) introduces recent suboptimal control and simulation-based approximation techniques (neuro-dynamic programming), which allow the practical application of dynamic programming to complex problems that involve the dual curse of large dimension and lack of an accurate mathematical model, 5) provides a comprehensive treatment of infinite horizon problems in the second volume, and an introductory treatment in the first volume The electronic version of the book includes 29 theoretical problems, with high-quality solutions, which enhance the range of coverage of the book.

Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners." —Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of uncertainty. Approximate Dynamic Programming, Second Edition uniquely integrates four distinct disciplines—Markov decision processes, mathematical programming, simulation, and statistics—to demonstrate how to successfully approach, model, and solve a wide range of real-life problems using ADP. The book continues to bridge the gap between computer science, simulation, and operations research and now adopts the notation and vocabulary of reinforcement learning as well as stochastic search and simulation optimization. The author outlines the essential algorithms that serve as a starting point in the design of practical solutions for real problems. The three curses of dimensionality that impact complex problems are introduced and detailed coverage of implementation challenges is provided. The Second Edition also features: A new chapter describing four fundamental classes of policies for working with diverse stochastic optimization problems: myopic policies, look-ahead policies, policy function approximations, and policies based on value function approximations A new chapter on policy search that brings together stochastic search and simulation optimization concepts and introduces a new class of optimal learning strategies Updated coverage of the exploration exploitation problem in ADP, now including a recently developed method for doing active learning in the presence of a physical state, using the concept of the knowledge gradient A new sequence of chapters describing statistical methods for approximating value functions, estimating the value of a fixed policy, and value function approximation while searching for optimal policies The presented coverage of ADP emphasizes models and algorithms, focusing on related applications and computation while also discussing the theoretical side of the topic that explores proofs of convergence and rate of convergence. A related website features an ongoing discussion of the evolving fields of approximation dynamic programming and reinforcement learning, along with additional readings, software, and datasets. Requiring only a basic understanding of statistics and probability, Approximate Dynamic Programming, Second Edition is an excellent book for industrial engineering and operations research courses at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals who utilize dynamic programming, stochastic programming, and control theory to solve problems in their everyday work.

Vols. for 1898-1968 include a directory of publishers.