open_spiel
tensortrade
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open_spiel | tensortrade | |
---|---|---|
44 | 44 | |
3,983 | 4,368 | |
1.1% | 1.2% | |
9.4 | 0.0 | |
8 days ago | 3 months ago | |
C++ | Python | |
Apache License 2.0 | Apache License 2.0 |
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open_spiel
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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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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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Policy for each of multi-agents in RL
The RL agents in OpenSpiel (https://github.com/deepmind/open_spiel) are designed with this setting as the default (so like, DQN run in Tic-Tac-Toe would have two separate agents learning against each other: one knows how to play as player 1, the other as player 2).
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My comp sci mentor who is a university student half my age says that learning to use Linux is the optimal comp sci education experience
I maintain a project called OpenSpiel, basically a library/suite of implementations of board games (mainly for AI research but can be used for whatever). It has a C/C++ core, but it also exposes the core API in Python, Rust, Go, and Julia: https://github.com/deepmind/open_spiel/ and a lot of AI algorithms in Python.
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Looking to get started
If you are looking for some programming game-theoretic algorithms, you can look at Gambit (http://www.gambit-project.org/) or OpenSpiel (https://github.com/deepmind/open_spiel). OpenSpiel has a Julia API too exposing the core and games, but does not have any of the basic game theoretic algorithms in Julia, so that would make a nice exercise (and maybe contribution to the project).
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[D] Adding a new RL environment to envpool
I looked at the paper before and thought some of the benchmarks in the paper were cherry picked and that the whole let’s write env in compiled languages things has been done a lot already and only works well for games / physics / environments that are extremely well defined . I usually end up back in ray env bc I usually need features like parametric action spaces, or predictive models built inside environments, or historical data. Codingwise I looked at the example file that they had and felt like it wasn’t for me bc I don’t like Bazel ( I use pants for python monorepo ) and the c++ api was overly verbose for me. I don’t feel like I could implement reward shaping or env business logic in a very clear way. I don’t do much c++ dev work though and someone who is a seasoned c++ dev might not care. I liked the openspiel c++ api for env a lot more. https://github.com/deepmind/open_spiel/blob/master/docs/developer_guide.md I have found that building a new env can sometimes be frustrating to debug and I would probably debug a python env before converting to an openspiel/envpool env if I had to use a C++ env for a new problem.
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Mastering Stratego, the classic game of imperfect information
I 404'ed when I tried to access the source code?
https://github.com/deepmind/open_spiel/tree/master/open_%20s...
Someone needs to create a web front end for this -- I would love to play it.
There's an extra space in the URL to their code (at the end of the article). The correct URL is: https://github.com/deepmind/open_spiel/tree/master/open_spie...
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Looking for Deepmind implementation of Player of Games
This is a wild guess. I am fairly sure that internally Deepmind uses their own tool, OpenSpiel. The code is kind of dense because it does a lot, but probably most of the functionality that you are looking for is somewhere in there
tensortrade
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Does anyone have experience with Reinforcement Learning (RL)?
Another one is https://github.com/tensortrade-org/tensortrade
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8+ Reinforcement Learning Project Ideas
Predict stock prices with TensorTrade
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Looking for reinforcement learning resource in finance
Looks like this is still being contributed to. It's a good start but lacks some parts.
What are some alternatives?
FinRL - FinRL: Financial Reinforcement Learning. 🔥
muzero-general - MuZero
FinRL - Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥 [Moved to: https://github.com/AI4Finance-Foundation/FinRL]
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
FinRL-Library - Deep Reinforcement Learning Framework to Automate Trading in Quantitative Finance. NeurIPS 2020 & ICAIF 2021. 🔥 [Moved to: https://github.com/AI4Finance-Foundation/FinRL]
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
Deep-Hedging
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver
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.