D4RL
A collection of reference environments for offline reinforcement learning (by Farama-Foundation)
open_spiel
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. (by google-deepmind)
| D4RL | open_spiel | |
|---|---|---|
| 2 | 44 | |
| 1,203 | 4,030 | |
| 2.8% | 1.5% | |
| 0.0 | 9.5 | |
| 3 months ago | 6 days ago | |
| Python | C++ | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
D4RL
Posts with mentions or reviews of D4RL.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-12-20.
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[D] Adding a new RL environment to envpool
Envpool provides high parallelization of RL environments. Unfortunately, there are still many environments that are not supported by them. One of them is FrankaKitchen of D4RL, a library for offline RL.
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Goal-Conditionned policy on Ant Maze
Links:D4RL environments: https://github.com/rail-berkeley/d4rlD4RL DDPG implementation I'm talking about: https://github.com/rail-berkeley/d4rl_evaluations/tree/master/bcq/continuous_bcq
open_spiel
Posts with mentions or reviews of open_spiel.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-26.
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What projects or open-source contributions can impress Jane Street recruiters for a Quant SWE role ?
Deep mind actually has a repository where they applied this algorithm for incomplete-knowledge games. You could use it for reference: https://github.com/deepmind/open_spiel/tree/master/open_spiel/python/algorithms
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I want to build a learning agent for a combinatorial game
+1. You can also find an implementation of Clobber and AlphaZero (and many other basic RL algorithms) in OpenSpiel: https://github.com/deepmind/open_spiel
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minimax for imperfect-information turn-games?
You can find a lot of code online if you look, and many of these applied to Poker. There's a general implementation of both in Python and C++ in OpenSpiel, with some examples applied to small poker games. It's nice code to learn from because the algorithms operate over generic game descriptions, so there aren't game-specific design choices mixed up with the implementation of the algorithms, and you can create your own poker game and just run them on it.
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OpenSpiel 1.3 Released!
And many other additions and improvements. See all the details here: https://github.com/deepmind/open_spiel/releases/tag/v1.3
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What's a good OpenAI Gym Environment for applying centralized multi-agent learning using expected SARSA with tile coding?
I would checkout the openspiel package. It's main focus is RL in games (multi-agent environments). You'll find RL examples there and games that are small enough to solve without deep RL. There's also a wide range of environments from fully cooperative to adversarial zero-sum.
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Competitive reinforcement learning for turn-based games
Hi, you can check out OpenSpiel: https://github.com/deepmind/open_spiel/
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Reinforcement learning and Game Theory a turn-based game
as for algorithms , openspiel repository has few implementations some of these are not related to imperfect information games , and others are not for multiagent environment and others are tabular algorithms .
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
This includes single-agent Gymnasium wrappers for DM Control, DM Lab, Behavior Suite, Arcade Learning Environment, OpenAI Gym V21 & V26. Multi-agent PettingZoo wrappers support DM Control Soccer, OpenSpiel and Melting Pot. For more information, read the release notes here:
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How to deal with situations where the RL agent cannot act at every time step?
I've had some success using Action Masking - you can refer to here https://github.com/deepmind/open_spiel/blob/120420a74a69354d64c10b51cd129d4587f9f325/open_spiel/python/algorithms/dqn.py but for DQN you need to mask out q values for invalid actions (as well as masking them during prediction). In my case I'm able to place my mask in the observation so can fetch it quite easily during prediction but if that's not possible you could query it from the environment and store it in the replay buffer (like they do in the link I shared)
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How to search the game tree with depth-first search?
Take a look at this simple implementation: https://github.com/deepmind/open_spiel/blob/master/open_spiel/algorithms/minimax.cc
What are some alternatives?
When comparing D4RL and open_spiel you can also consider the following projects:
D4RL-Evaluations
muzero-general - MuZero
envpool - C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
gym - A toolkit for developing and comparing reinforcement learning algorithms.
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
gym-battleship - Battleship environment for reinforcement learning tasks
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver
tensortrade - An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
ml-agents - The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
AirSim - Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research