open_spiel
lab
open_spiel | lab | |
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44 | 4 | |
4,030 | 7,002 | |
1.5% | 0.0% | |
9.5 | 0.0 | |
1 day ago | over 1 year ago | |
C++ | C | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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open_spiel
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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
lab
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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:
- Environments that require long-term memory and reasoning
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Keys doors puzzle in dmlab30
dmlab30 is a test suite of 30 environments for Deep RL research, maintained by DeepMind. https://github.com/deepmind/lab/tree/master/game_scripts/levels/contributed/dmlab30#readme
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[R] Would DeepMind Control Suite be enough for a publication?
DeepMind Lab is also interesting: https://deepmind.com/blog/article/open-sourcing-deepmind-lab https://github.com/deepmind/lab
What are some alternatives?
muzero-general - MuZero
ruby-fann - Ruby library for interfacing with FANN (Fast Artificial Neural Network)
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
PHP IDS - PHPIDS (PHP-Intrusion Detection System) is a simple to use, well structured, fast and state-of-the-art security layer for your PHP based web application
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
gym-battleship - Battleship environment for reinforcement learning tasks
CCV - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver
dm_memorytasks - A set of 13 diverse machine-learning tasks that require memory to solve.