Q-Transformer: Scalable Reinforcement Learning via Autoregressive Q-Functions

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • RWKV-LM

    RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.

  • This is what RWKV (https://github.com/BlinkDL/RWKV-LM) was made for, and what it will be good at.

    Wow. Pretty darn cool! <3 :'))))

  • SimpleReinforcementLearning

    A demonstration of table based, SARSA reinforcement learning for a simple cat/mouse game

  • +1 you beat me to the punch! I think its helpful to start with simple RL and ignore the "deep" part to get the basics. The first several lectures in this series do that well. It helped me build a simple "cat and mouse" RL simulation https://github.com/gtoubassi/SimpleReinforcementLearning and ultimately a reproduction of the DQN atari game playing agent: https://github.com/gtoubassi/dqn-atari.

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  • dqn-atari

    A TensorFlow based implementation of the DeepMind Atari playing "Deep Q Learning" agent that works reasonably well (by gtoubassi)

  • +1 you beat me to the punch! I think its helpful to start with simple RL and ignore the "deep" part to get the basics. The first several lectures in this series do that well. It helped me build a simple "cat and mouse" RL simulation https://github.com/gtoubassi/SimpleReinforcementLearning and ultimately a reproduction of the DQN atari game playing agent: https://github.com/gtoubassi/dqn-atari.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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