This repo contains code for the E3B algorithm described in the NeurIPS 2022 paper Exploration via Elliptical Episodic Bonuses by Mikael Henaff, Roberta Raileanu, Minqi Jiang and Tim Rocktäschel.
E3B is an exploration algorithm designed for contextual MDPs, where the environment changes every episode. Examples of contextual MDPs include procedurally-generated environments such as MiniGrid, MiniHack, NetHack, ProcGen, and embodied AI settings such as Habitat where the agent finds itself in a new indoor space each episode.
The algorithm is simple to implement and operates using an elliptical bonus computed at the episode level, in a feature space induced by an inverse dynamics model.
Code to run E3B on MiniHack and Vizdoom uses IMPALA as the base RL algorithm and is contained in the minihack folder. Code to run E3B on Habitat uses DD-PPO and is in the habitat-lab folder. Please see the README files in each folder for further instructions.
If you use this code in your work, please cite the following:
@inproceedings{E3B,
title = {Exploration via Elliptical Episodic Bonuses},
author = {Mikael Henaff and Roberta Raileanu and Minqi Jiang and Tim Rocktäschel},
booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
year = {2022}
}
This repo is built on the Torchbeast code. We also use parts of the RIDE and NovelD codebases for baselines.
The majority of this project is licensed under CC-BY-NC, however portions of the project are available under separate license terms: NovelD is licensed under the Apache 2.0 license.