DRLA Simulator

Trains a deep reinforcement learning agent in simulation testbed environments with the DRLA library.

The following environments are available:

• Cart Pole
• Tic Tac Toe
• Connect Four
• Grid World (WIP)

Building and Using

Install libtorch at /usr/local/libtorch and ensure cmake is also installed.

cmake --preset release
cmake --build --preset release --target install --parallel 8

Dependencies

All below dependencies are fetched automatically via cmake fetch content.

• drla
• nlohmann-json
• spdlog
• cxxopts

Training

To run training pass the config json file and the path to store the training data:

../install/drla-sim/bin/sim_train --config /path/to/config.json --data /path/to/data/directory/

An example config for connect4 can be found here.

Monitoring training

Run Tensorboard to view current and previous training runs:

tensorboard --max_reload_threads 4 --load_fast=false --bind_all --logdir /path/to/data/directory/

Goto http://localhost:6006 to view webpage.

Running an agent

A trained agent can be run via:

../install/drla-sim/bin/sim_run --data /path/to/data/directory/