Computation Techniques for Large Scale Undiscounted Markov Decision Processes.
Abstract
This paper considers computation techniques associated with the optimization of large scale Markov decision processes. Markov decision processes and successive approximation procedures are described. Then a procedure for scaling continuous time and renewal processes so that they are amenable to the second procedure is discussed. The effect of the scale factor value on the convergence rate of the procedure and insights into proper scale factor selection are given. Finally, various methods of achieving computational efficiency during execution of the optimization are considered.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1978
- Accession Number
- ADA052895
Entities
People
- Gary J. Koehler
- Thom J. Hodgson
Organizations
- University of Florida