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qfettes / DeepRL-Tutorials

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Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
reinforcement-learning gae deep-reinforcement-learning rainbow python3 pytorch deep-q-network actor-critic double-dqn quantile-regression dueling-dqn categorical-dqn ppo advantage-actor-critic a2c deep-recurrent-q-network prioritized-experience-replay multi-step-learning noisy-networks deeprl-tutorials
  • Updated Feb 21, 2020
  • Jupyter Notebook

TheMTank / cups-rl

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Customisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"
agent wrapper natural-language-processing reinforcement-learning robotics simulation cup rainbow pytorch a3c transfer-learning cups multi-task-learning model-based model-free simulated-environments natural-language-instructions ai2thor-environment openai-gym-interface
  • Updated Mar 9, 2020
  • Python

SitecoreUnicorn / Rainbow

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Rainbow doesn't warn me when critical path length settings are different than expected

cassidydotdk
cassidydotdk commented Nov 11, 2018

Do you want to request a feature or report a bug?
A quality of life improvement

What is the current behavior?
Today, it is possible for users (developers, usually) to change the Rainbow.config settings for SerializationFolderPathMaxLength and MaxItemNameLengthBeforeTruncation (presumably to accommodate for a long local root path) and forgetting that this setting needs to be _the s

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enhancement

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