Borkar, Vivek S. ; Pinto, Jervis ; Prabhu, Tarun (2009) A new learning algorithm for optimal stopping Discrete Event Dynamic Systems: Theory and Applications, 19 (1). pp. 91-113. ISSN 0924-6703
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Official URL: http://www.springerlink.com/content/j2gg544w222725...
Related URL: http://dx.doi.org/10.1007/s10626-008-0055-2
Abstract
A linear programming formulation of the optimal stopping problem for Markov decision processes is approximated using linear function approximation. Using this formulation, a reinforcement learning scheme based on a primal-dual method and incorporating a sampling device called 'split sampling'is proposed and analyzed. An illustrative example from option pricing is also included.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Springer-Verlag. |
| Keywords: | Learning Algorithm; Optimal Stopping; Linear Programming; Primal-dual Methods; Split Sampling; Option Pricing |
| ID Code: | 5368 |
| Deposited On: | 18 Oct 2010 09:01 |
| Last Modified: | 20 May 2011 08:45 |
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