The project is currently in development. Right now I have implemented a variant of off-policy actor-critic, and pUCT Monte-Carlo Tree Search (MCTS) to use the actor-critic predictions as the basis of a lookahead search. This use of MCTS is used in a similar way to AlphaZero. My future work involves:
- Refactoring the codebase
- Implementing a variant of the AlphaZero algorithm
- Implementing DQN, and various algorithms
- Writing a survey paper on various RL approaches in this environment
To test my work so far, clone down this repository. You will need an environment with torch, numpy, and tensorboard installed.
Try python3 test.py.
A graphical interface for the game should pop up, where you can then play against my agent to see how well it performs against you in ConnectFour.