mcimpoi / unreal

Reinforcement learning with unsupervised auxiliary tasks

UNREAL / A3C / A3C-LSTM agent for MINOS

This is an implementation of the UNREAL agent described in Reinforcement Learning with Unsupervised Auxiliary Tasks by Jaderberg et al. 2016 for use with the MINOS multimodal indoor simulator. This implementation is directly adaptated from https://github.com/miyosuda/unreal with a thin gym wrapper around the MINOS framework. The original implementation README.md file is here. This code also implements the A3C and A3C-LSTM baseline agents (as ablations of the full UNREAL agent -- see options.py for relevant flags).

Installation

Follow the MINOS installation instructions. Confirm that the minos package is available by running python3 -c 'import minos; print(minos)'.

Running experiments

Start experiments using invocations such as the following:

python3 main.py --env_type indoor --env_name pointgoal_suncg_se

python3 main.py --env_type indoor --env_name objectgoal_suncg_mf

python3 main.py --env_type indoor --env_name roomgoal_mp3d_s

Refer to options.py for available arguments that control the hyperparameters and agent architecture.