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Found 2 papers, 1 papers with code
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
Iteratively improving and repairing source code with large language models (LLMs), known as refinement, has emerged as a popular way of generating programs that would be too complex to construct in one shot.
Constrained Model-based Reinforcement Learning with Robust Cross-Entropy Method
We propose a model-based approach to enable RL agents to effectively explore the environment with unknown system dynamics and environment constraints given a significantly small number of violation budgets.
Model-based Reinforcement Learning
Model Predictive Control
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