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1. gym-continuousDoubleAuctiongym-continuousDoubleAuctionPublic

   A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

   Jupyter Notebook 144 31

2. reinforcement_learningreinforcement_learningPublic

   My reproduction of various reinforcement learning algorithms (DQN variants, A3C, DPPO, RND with PPO) in Tensorflow.

   Jupyter Notebook 38 11

3. PBT_MARL_watered_downPBT_MARL_watered_downPublic

   My attempt to reproduce a water down version of PBT (Population based training) for MARL (Multi-agent reinforcement learning) using DDPPO (Decentralized & distributed proximal policy optimization) …

   Jupyter Notebook 8 1

4. sagemaker_Ray_RLlib_custom_envsagemaker_Ray_RLlib_custom_envPublic

   Sample setup for custom reinforcement learning environment in Sagemaker. This example uses Proximal Policy Optimization with Ray (RLlib).

   Python 2 2

5. OrderBookOrderBookPublic

   Forked fromdyn4mik3/OrderBook

   Matching Engine for Limit Order Book

   Python 1

6. web_app_DPDTHweb_app_DPDTHPublic

   Sample CI/CD devops setup of Django & Postgres web app with Docker, Travis & Heroku.

   JavaScript 4 4