This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms. This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. Among its special features, the book: 1) Quantifies the performance of parallel algorithms, including the limitations imposed by the communication and synchronization penalties. 2) Describes communication algorithms for a variety of system architectures including tree, mesh, and hypercube. 3) Provides a comprehensive convergence analysis of asynchronous methods and a comparison with their asynchronous counterparts. 4) Cove

Parallel and Distributed Computation: Numerical Methods (Optimization and Neural Computation)

Dimitri P. Bertsekas

Bertsekas, Dimitri P.

John Tsitsiklis

Tsitsiklis, John

Computers & Technology

Athena Scientific

This is the first textbook that fully explains the neuro-dynamic programming/reinforcement learning methodology, which is a recent breakthrough in the practical application of neural networks and dynamic programming to complex problems of planning, optimal decision making, and intelligent control. 
Neuro-dynamic programming uses neural network approximations to overcome the "curse of dimensionality" and the "curse of modeling" that have been the bottlenecks to the practical application of dynamic programming and stochastic control to complex problems. The methodology allows systems to learn about their behavior through simulation, and to improve their performance through iterative reinforcement. 
This book provides the first systematic presentation of the science and the art behind this exciting and far-reaching methodology. 
The book develops a comprehensive analysis of neuro-dynamic programming algorithms, and guides the reader to their successful application through case studies from complex problem areas.

Neuro-Dynamic Programming (Optimization and Neural Computation Series, 3)

Science & Math

John N. Tsitsiklis

Tsitsiklis, John N.

Mathematics

This book provides a unified, insightful, and modern treatment of linear optimization, that is, linear programming, network flow problems, and discrete optimization. It includes classical topics as well as the state of the art, in both theory and practice.

Introduction to Linear Optimization (Athena Scientific Series in Optimization and Neural Computation, 6)

Dimitris Bertsimas

Bertsimas, Dimitris

See the best price to sell, buy, or rent books by John Tsitsiklis. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by John Tsitsiklis