NeurIPS 2015
Policy Evaluation Using the Ω-Return
Abstract
We propose the Ω-return as an alternative to the λ-return currently used by the TD(λ) family of algorithms. The benefit of the Ω-return is that it accounts for the correlation of different length returns. Because it is difficult to compute exactly, we suggest one way of approximating the Ω-return. We provide empirical studies that suggest that it is superior to the λ-return and γ-return for a variety of problems.
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Context
- Venue
- Annual Conference on Neural Information Processing Systems
- Archive span
- 1987-2025
- Indexed papers
- 30776
- Paper id
- 1111637546766369065