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Network Control and Optimization
This book constitutes the refereed proceedings of the First Euro-FGI International Conference on Network Control and Optimization, NET-COOP 2007, held in Avignon, France in June 2007. The 22 revised full papers presented together with nine invited lectures address all current issues in network control and optimization, ranging from performance evaluation and optimization of general stochastic networks to more specific targets.
Statistics, Probability, and Game Theory
Most of the 26 papers are research reports on probability, statistics, gambling, game theory, Markov decision processes, set theory, and logic. But they also include reviews on comparing experiments, games of timing, merging opinions, associated memory models, and SPLIF's; historical views of Carnap, von Mises, and the Berkeley Statistics Department; and a brief history, appreciation, and bibliography of Berkeley professor Blackwell. A sampling of titles turns up The Hamiltonian Cycle Problem and Singularly Perturbed Markov Decision Process, A Pathwise Approach to Dynkin Games, The Redistribution of Velocity: Collision and Transformations, Casino Winnings at Blackjack, and Randomness and the Foundations of Probability. No index. Annotation copyrighted by Book News, Inc., Portland, OR
Stochastic Dynamic Programming and the Control of Queueing Systems
A path-breaking account of Markov decision processes-theory and computation This book's clear presentation of theory, numerous chapter-end problems, and development of a unified method for the computation of optimal policies in both discrete and continuous time make it an excellent course text for graduate students and advanced undergraduates. Its comprehensive coverage of important recent advances in stochastic dynamic programming makes it a valuable working resource for operations research professionals, management scientists, engineers, and others. Stochastic Dynamic Programming and the Control of Queueing Systems presents the theory of optimization under the finite horizon, infinite hori...
A Portal to Paradise
Arizona's rugged Chiricahua Mountains have a special place in frontier history. They were the haven of many well-known personalities, from Cochise to Johnny Ringo, as well as the home of prospectors, cattlemen, and hardscrabble farmers eking out a tough living in an unforgiving landscape. In this delightful and well-researched book, Alden Hayes shares his love for the area, gained over fifty years. From his vantage point near the tiny twin communities of Portal and Paradise on the eastern slopes of the Chiricahuas, Hayes brings the famous and the not-so-famous together in a profile of this striking landscape, showing how place can be a powerful formative influence on people's lives. When Hay...
Modern Trends in Controlled Stochastic Processes
World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, controlled diffusions, piece-wise deterministic processes etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several numerical methods, index-based approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization and Information Transmission. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.
Planning with Markov Decision Processes
Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent should behave to achieve its objectives. On the other hand, reinforcement learning additionally learns these models based on...
Network Control and Optimization
This book constitutes the refereed proceedings of the Second Euro-NF International Conference, NET-COOP 2008 held in Paris, France, in September 2008. The 13 revised full papers presented were carefully reviewed and selected from a total of 27 submissions. The papers are organized in topical sections on economics and peer-to-peer networks; routing and measurements; scheduling; tcp and congestion control; as well as wireless networks.
Interest-Rate Management
This book combines a rigorous overview of the mathematics of financial markets with an insight into the practical application of these models to the risk and portfolio management of interest-rate derivatives. It can also serve as a valuable textbook on financial markets for graduate and PhD students in mathematics. Interesting and comprehensive case studies illustrate the theoretical concepts.
