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Sandbox Saya without any graphics. Trying to code a way to use reinforcement learning with Q Networking and MCTS in Real time strategy games. Bellman Equation to predict future prediction of state and action pairs. Comparison for DQN and PPO.

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Skyfrei/Saya

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Simplified Saya version with DQN and PPO

Sandbox Saya without any graphics. Trying to code a way to use reinforcement learning and MTCS in Real time strategy games.

Game will not have any graphics for a long time if ever because the point of the project is to create an RTS game which can be deeplearned with different algorithms, following previously published licensed papers. At the end of the project the AI will be able to go toe to toe with a human enemy and make the best possible decisions to win the game.

How can you collaborate

  • Bug finding in the game in case i have missed something such as times when Id get undefined behaviours.
  • Probably nulll pointer mem access here as i have implemented null pointers for actions.
  • Ideas on how to continue the Reinforcement learning and stuff i could add to it. Maybe additions to algorithms DQN and PPO and maybe ideas about adding SARSA too.
  • Better writing of structs and enums (this would actually be really helpful)
  • Structuing of header files and where classes go to, specifically the unit header.

What has currently been implemented

  • Game is fully finished and playable although not very interesting without graphics as its a real time strategy game.
  • Algorithm for reinforcement learning has been implemented
  • PyTorch has been sucessfully started running.
  • Currently changing the input of the game so it fits in my tensor model.

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Sandbox Saya without any graphics. Trying to code a way to use reinforcement learning with Q Networking and MCTS in Real time strategy games. Bellman Equation to predict future prediction of state and action pairs. Comparison for DQN and PPO.

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