360ZMEM/LLMRsearcher-code
Langchain implementation of the paper "LLMs as Efficient Reward Function Searchers for Custom-Environment MORL".
This tool helps researchers and engineers quickly design and refine reward functions for complex Multi-Objective Reinforcement Learning (MORL) environments. It takes your high-level problem description and environment details, and outputs optimized reward function code and appropriate weightings for different objectives. This is intended for professionals working on advanced AI training in domains like robotics or operational optimization.
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Use this if you are developing or evaluating AI agents in a custom environment where traditional reward function design is time-consuming and inefficient.
Not ideal if you are looking for a pre-built solution for a standard reinforcement learning problem with well-defined reward structures.
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Python
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Last pushed
Jan 05, 2025
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