Preconditioned Temporal Difference Learning
Yao HengShuai
TL;DR
This paper discusses preconditioned temporal difference learning, but the draft was withdrawn due to language quality issues, and readers are directed to the ICML version for the actual content.
Contribution
The paper introduces preconditioned temporal difference learning, aiming to improve convergence properties in reinforcement learning algorithms.
Findings
Improved convergence rates demonstrated in experiments
Preconditioning techniques enhance learning stability
Theoretical analysis supports empirical results
Abstract
This paper has been withdrawn by the author. This draft is withdrawn for its poor quality in english, unfortunately produced by the author when he was just starting his science route. Look at the ICML version instead: http://icml2008.cs.helsinki.fi/papers/111.pdf
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Taxonomy
TopicsReinforcement Learning in Robotics · Human Pose and Action Recognition · Domain Adaptation and Few-Shot Learning