Simulation-based Algorithms for Markov Decision Processes

• Main Authors: Chang, Hyeong Soo (Author), Hu, Jiaqiao (Author), Fu, Michael C. (Author), Marcus, Steven I. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2007.
• Series: Communications and Control Engineering,
• Subjects: Business.; Operations research.; Decision making.; Algorithms.; System theory.; Management science.; Probabilities.; Control engineering.; Business and Management.; Operation Research/Decision Theory.; Control.; Systems Theory, Control.; Operations Research, Management Science.; Probability Theory and Stochastic Processes.; Algorithm Analysis and Problem Complexity.

Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. It is well-known that many real-world problems modeled by MDPs have huge state and/or action spaces, leading to the n...

Table of Contents:

• Markov Decision Processes
• Multi-stage Adaptive Sampling Algorithms
• Population-based Evolutionary Approaches
• Model Reference Adaptive Search
• On-line Control Methods via Simulation.