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cs.LG2026
Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias
Rahaf Abu Hara, Vaibbhav Murarri, Claudio Zito
Existing LLM-based policy optimizers see only scalar rewards: that a policy scored 0.45, but not whether the agent got stuck in a loop, fell into a hole on the third step, or perfo…
cs.LG2022
Dyna-T: Dyna-Q and Upper Confidence Bounds Applied to Trees
Tarek Faycal, Claudio Zito
In this work we present a preliminary investigation of a novel algorithm called Dyna-T. In reinforcement learning (RL) a planning agent has its own representation of the environmen…