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Minigrid & miniworld: modular & customizable reinforcement learning environments for goal-oriented tasks

Minigrid & miniworld: modular & customizable reinforcement learning environments for goal-oriented tasks
Minigrid & miniworld: modular & customizable reinforcement learning environments for goal-oriented tasks
We present the Minigrid and Miniworld libraries which provide a suite of goal-oriented 2D and 3D environments. The libraries were explicitly created with a minimalistic design paradigm to allow users to rapidly develop new environments for a wide range of research-specific needs. As a result, both have received widescale adoption by the RL community, facilitating research in a wide range of areas. In this paper, we outline the design philosophy, environment details, and their world generation API. We also showcase the additional capabilities brought by the unified API between Minigrid and Miniworld through case studies on transfer learning (for both RL agents and humans) between the different observation spaces. The source code of Minigrid and Miniworld can be found at https://github.com/Farama-Foundation/{Minigrid, Miniworld} along with their documentation at https://{minigrid, miniworld}.farama.org/.
Computer Science - Machine Learning
Neural Information Processing Systems Foundation
Chevalier-Boisvert, Maxime
37ecc2ba-1f19-4875-bb53-ead13c373f21
Dai, Bolun
26eeb823-f029-48df-85f2-55be3731a1e0
Towers, Mark
18e6acc7-29c4-4d0c-9058-32d180ad4f12
de Lazcano, Rodrigo
8cac3e42-07fc-427d-8ce6-4431b25c0c7f
Willems, Lucas
aa237ba1-9df2-41f9-afbe-8cc8c57e2030
Lahlou, Salem
3c4291bd-8b7c-4616-bd99-2cce012a0dfd
Pal, Suman
3ebb67b2-4932-40b7-bc1e-5e0e4eb6aeb5
Castro, Pablo Samuel
7801c3a8-2a71-4240-b9dc-07784dc10692
Terry, Jordan
b8c1b91b-5473-449b-8733-c23f96f7424b
Oh, A.
Neumann, T.
Globerson, A.
Saenko, K.
Hardt, M.
Levine, S.
Chevalier-Boisvert, Maxime
37ecc2ba-1f19-4875-bb53-ead13c373f21
Dai, Bolun
26eeb823-f029-48df-85f2-55be3731a1e0
Towers, Mark
18e6acc7-29c4-4d0c-9058-32d180ad4f12
de Lazcano, Rodrigo
8cac3e42-07fc-427d-8ce6-4431b25c0c7f
Willems, Lucas
aa237ba1-9df2-41f9-afbe-8cc8c57e2030
Lahlou, Salem
3c4291bd-8b7c-4616-bd99-2cce012a0dfd
Pal, Suman
3ebb67b2-4932-40b7-bc1e-5e0e4eb6aeb5
Castro, Pablo Samuel
7801c3a8-2a71-4240-b9dc-07784dc10692
Terry, Jordan
b8c1b91b-5473-449b-8733-c23f96f7424b
Oh, A.
Neumann, T.
Globerson, A.
Saenko, K.
Hardt, M.
Levine, S.

Chevalier-Boisvert, Maxime, Dai, Bolun, Towers, Mark, de Lazcano, Rodrigo, Willems, Lucas, Lahlou, Salem, Pal, Suman, Castro, Pablo Samuel and Terry, Jordan (2023) Minigrid & miniworld: modular & customizable reinforcement learning environments for goal-oriented tasks. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. and Levine, S. (eds.) In Advances in Neural Information Processing Systems 36 (NeurIPS 2023). Neural Information Processing Systems Foundation. 12 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

We present the Minigrid and Miniworld libraries which provide a suite of goal-oriented 2D and 3D environments. The libraries were explicitly created with a minimalistic design paradigm to allow users to rapidly develop new environments for a wide range of research-specific needs. As a result, both have received widescale adoption by the RL community, facilitating research in a wide range of areas. In this paper, we outline the design philosophy, environment details, and their world generation API. We also showcase the additional capabilities brought by the unified API between Minigrid and Miniworld through case studies on transfer learning (for both RL agents and humans) between the different observation spaces. The source code of Minigrid and Miniworld can be found at https://github.com/Farama-Foundation/{Minigrid, Miniworld} along with their documentation at https://{minigrid, miniworld}.farama.org/.

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Published date: 1 June 2023
Keywords: Computer Science - Machine Learning

Identifiers

Local EPrints ID: 488105
URI: http://eprints.soton.ac.uk/id/eprint/488105
PURE UUID: a83c39b1-446a-4ec2-bb71-799f6482c080
ORCID for Mark Towers: ORCID iD orcid.org/0000-0002-2609-2041

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Date deposited: 15 Mar 2024 17:46
Last modified: 10 Apr 2024 02:04

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Contributors

Author: Maxime Chevalier-Boisvert
Author: Bolun Dai
Author: Mark Towers ORCID iD
Author: Rodrigo de Lazcano
Author: Lucas Willems
Author: Salem Lahlou
Author: Suman Pal
Author: Pablo Samuel Castro
Author: Jordan Terry
Editor: A. Oh
Editor: T. Neumann
Editor: A. Globerson
Editor: K. Saenko
Editor: M. Hardt
Editor: S. Levine

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