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2025 ICML ICML 2025

The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Pedro Pinto Santos, Alberto Sardinha, Francisco S. Melo

Topics

Reinforcement Learning > Methods > Policy Learning Reinforcement Learning > Applications > Robotics

Keywords

average frequencies discounted frequencies finite-horizon gumdps general-utility markov decision processes infinite-horizon gumdps number of trials
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