Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead
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arXiv:2609.11807v1 Announce Type: new Abstract: We study reinforcement learning (RL) with transition look-ahead, where the agent may observe which states would be visited upon playing any sequence of $\ell$ actions before deciding its course of action. Although look-ahead can substantially improve…
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- 2026-09-11 04:00 · arXiv stat.ML
Near-Optimal Reinforcement Learning with Multi-Step Transition Lookahead