Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Simulation-Based Algorithms for Markov Decision Processes

Simulation-Based Algorithms for Markov Decision Processes

Chang, Hyeong Soo
Fu, Michael C.
Hu, Jiaqiao

Paperback

Series: Communications and Control Engineering

Technology & EngineeringGeneral Computers

Currently unavailable to order

ISBN10: 1849966435
ISBN13: 9781849966436
Publisher: Springer
Published: Oct 19 2010
Pages: 189
Weight: 0.66
Height: 0.44 Width: 6.10 Depth: 9.25
Language: English

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. This book provides practical modeling methods for many real-world problems with high dimensionality or complexity which have not hitherto been treatable with Markov decision processes. In addition to providing numerous specific algorithms, coverage includes both illustrative numerical examples and rigorous theoretical convergence results. The algorithms developed and analyzed differ from the successful computational methods for solving MDPs based on neuro-dynamic programming or reinforcement learning and will complement work in those areas. In addition, the book shows how to combine the various algorithms introduced with approximate dynamic programming methods that reduce the size of the state space and ameliorate the effects of dimensionality.

Also in

Technology & Engineering

View All