TroddenSpade/Meta-Reinforcement-Learning
Code snippets of Meta Reinforcement Learning algorithms
This project provides code snippets for implementing various Meta Reinforcement Learning (MRL) algorithms from scratch using PyTorch. It helps machine learning researchers and practitioners understand and experiment with MRL techniques. You can input various MRL approaches and environmental parameters, and it outputs trained models and visualizations demonstrating adaptive learning in simulated environments.
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Use this if you are a machine learning researcher or student looking to implement, test, and understand core Meta Reinforcement Learning algorithms.
Not ideal if you need a production-ready MRL library or a high-level API for quick model deployment without diving into implementation details.
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Last pushed
Sep 07, 2023
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