Handbook of Markov Decision Processes Book

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Handbook of Markov Decision Processes, , Handbook of Markov Decision Processes

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Handbook of Markov Decision Processes
Written by author Egene A. Feinberg
Published by Springer Netherlands, June 2005
The theory of Markov Decision Processes - also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming - studies sequential optimization of discrete time stochastic

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1 Introduction 1
Pt. 1 Finite State and Action Models
2 Finite State and Action MDPs 21
3 Bias Optimality 89
4 Singular Perturbations of Markov Chains and Decision Processes 113
Pt. II Infinite State Models
5 Average Reward Optimization Theory for Denumerable State Spaces 153
6 Total Reward Criteria 173
7 Mixed Criteria 209
8 Blackwell Optimality 231
9 The Poisson Equation for Countable Markov Chains: Probabilistic Methods and Interpretations 269
10 Stability, Performance Evaluation, and Optimization 305
11 Convex Analytic Methods in Markov Decision Processes 347
12 The Linear Programming Approach 377
13 Invariant Gambling Problems and Markov Decision Processes 409
Pt. III Applications
14 Neuro-Dynamic Programming: Overview and Recent Trends 431
15 Markov Decision Processes in Finance and Dynamic Options 461
16 Applications of Markov Decision Processes in Communication Networks 489
17 Water Reservoir Applications of Markov Decision Processes 537
Index 559

Title: Handbook of Markov Decision Processes

Manufacturer:

Springer

Item Number: 9780792374596

Publication Date: June 2005

Number: 2

Product Description: Handbook of Markov Decision Processes

Universal Product Code (UPC): 9780792374596

WonderClub Stock Keeping Unit (WSKU): 9780792374596

Rating: 3/5 based on 2 Reviews

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Category: Media >> Books

Weight: 0.200 kg (0.44 lbs)

Width: 0.000 cm (0.00 inches)

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Depth: 0.000 cm (0.00 inches)

Date Added: August 25, 2020, Added By: Ross

Date Last Edited: August 25, 2020, Edited By: Ross

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Douglas E Maupin

reviewed Handbook of Markov Decision Processes on December 19, 2012

Handbook of Markov Decision Processes

READ JUN 2012

Classic piece from Kotter for any OD specialist. The system dynamic framework is a useful way to think about the connections between structures and key organizational processes. This framework can be used diagnostically as one seeks to understand the constraints and impacts each structure has on the other as well as on the key processes.

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1	Introduction	1
Pt. 1	Finite State and Action Models
2	Finite State and Action MDPs	21
3	Bias Optimality	89
4	Singular Perturbations of Markov Chains and Decision Processes	113
Pt. II	Infinite State Models
5	Average Reward Optimization Theory for Denumerable State Spaces	153
6	Total Reward Criteria	173
7	Mixed Criteria	209
8	Blackwell Optimality	231
9	The Poisson Equation for Countable Markov Chains: Probabilistic Methods and Interpretations	269
10	Stability, Performance Evaluation, and Optimization	305
11	Convex Analytic Methods in Markov Decision Processes	347
12	The Linear Programming Approach	377
13	Invariant Gambling Problems and Markov Decision Processes	409
Pt. III	Applications
14	Neuro-Dynamic Programming: Overview and Recent Trends	431
15	Markov Decision Processes in Finance and Dynamic Options	461
16	Applications of Markov Decision Processes in Communication Networks	489
17	Water Reservoir Applications of Markov Decision Processes	537
	Index	559