Repository contains reinforcement learning agents (A2C,DQN,DDPG,PPO), different forward models and artificial motivation modules from the knowledge-based category of intrinsic motivation. Models are being tested on robotic environments and Atari games.
Prerequisites are c++ compiler and swig then proceed with installation:
$ git clone https://github.com/Iskandor/MotivationModels.git
$ cd MotivationModels
$ pip install -r requirements.txt
$ python main.py --algorithm alg_name --env env_name --config config_id
Avaialable algorithms are ppo, ddpg, a2c, dqn
Environment names and ids of configuration can be found in config/alg_name.config.json
eg. ddpg.config.json
Project is still in development and we are planning to implement additional models and methods of reinforcement learning and intrinsic motivation.
Matej Pechac is doctoral student of informatics specializing in the area of reinforcement learning and intrinsic motivation
- univeristy webpage: http://dai.fmph.uniba.sk/w/Matej_Pechac/en
- contact: matej.pechac@gmail.com