Abstract
In this paper we extend temporal difference policy evaluation algorithms to performance criteria that include the variance of the cumulative reward. Such criteria are useful for risk management, and are important in domains such as finance and process control. We propose variants of both TD(0) and LSTD(λ) with linear function approximation, prove their convergence, and demonstrate their utility in a 4-dimensional continuous state space problem.
Original language | English |
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Pages (from-to) | 1532-1540 |
Number of pages | 9 |
Journal | Proceedings of Machine Learning Research |
Volume | 28 |
State | Published - 2013 |
Event | 30th International Conference on Machine Learning, ICML 2013 - Atlanta, GA, United States Duration: 16 Jun 2013 → 21 Jun 2013 |
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Sociology and Political Science