Temporal difference learning
PulseAugur coverage of Temporal difference learning — every cluster mentioning Temporal difference learning across labs, papers, and developer communities, ranked by signal.
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New Central Limit Theorem for TD Learning Published on arXiv
This paper, submitted to arXiv, presents a non-asymptotic central limit theorem for vector-valued martingale differences using Stein's method. The authors extend this to functions of Markov Chains and demonstrate its ap…
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New inference method improves temporal-difference learning accuracy
Researchers have developed a new method called Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning. This technique allows for more accurate inference from single Markov trajectories by accountin…
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New TRACE method enhances AI agent tool-use on long-horizon tasks · 2 sources tracked
Researchers have developed TRACE, a novel method for improving the performance of multi-turn AI agents in complex, long-horizon tasks. This technique addresses the challenge of credit assignment by deriving per-action r…
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New Framework Generates Complex Physics Word Problems Using LLMs and RL
Researchers have developed ARVRE, a novel framework for generating complex and solvable physics word problems. This two-stage system uses temporal-difference learning to create valid physics equation chains and an agent…
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TD learning fails to improve LLM few-shot retrieval on GSM8K
A researcher explored TD learning for improving retrieval of few-shot examples in LLM reasoning, aiming to assign learned values to traces based on their utility. The experiment involved storing reasoning traces, retrie…
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Lyapunov framework analyzes stochastic algorithm convergence
Researchers have published a paper detailing a Lyapunov-based framework for analyzing the finite-time convergence of stochastic iterative algorithms. This approach uses generalized Moreau envelopes as universal Lyapunov…