open_spiel
too-many-lists
open_spiel | too-many-lists | |
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44 | 219 | |
4,038 | 3,038 | |
1.7% | 1.3% | |
9.5 | 0.0 | |
2 days ago | about 1 month ago | |
C++ | Rust | |
Apache License 2.0 | MIT License |
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.
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
too-many-lists
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Towards memory safety with ownership checks for C
You seem to have a preset opinion, and I'm not sure you are interested in re-evaluating it. So this is not written to change your mind.
I've developed production code in C, C++, Rust, and several other languages. And while like pretty much everything, there are situations where it's not a good fit, I find that the solutions tend to be the most robust and require the least post release debugging in Rust. That's my personal experience. It's not hard data. And yes occasionally it's annoying to please the compiler, and if there were no trait constraints or borrow rules, those instances would be easier. But way more often in my experience the compiler complained because my initial solution had problems I didn't realize before. So for me, these situations have been about going from building it the way I wanted to -> compiler tells me I didn't consider an edge case -> changing the implementation and or design to account for that edge case. Also using one example, where is Rust is notoriously hard and or un-ergonomic to use, and dismissing the entire language seems premature to me. For those that insist on learning Rust by implementing a linked list there is https://rust-unofficial.github.io/too-many-lists/.
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Command Line Rust is a great book
Advent of Code was okay until I encounterd a problem that required a graph, tree or linked list to solve, where I hit a wall. Most coding exercises are similar--those requiring arrays and hashmaps and sets are okay, but complex data structures are a PITA. (There is an online course dedicated to linked lists in Rust but I couldn't grok it either). IMO you should simply skip problems that you can't solve with your current knowledge level and move on.
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[Media] I'm comparing writing a double-linked list in C++ vs with Rust. The Rust implementation looks substantially more complex. Is this a bad example? (URL in the caption)
I feel obligated to point to the original cannon literature: https://rust-unofficial.github.io/too-many-lists/
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Need review on my `remove()` implementation for singly linked lists
I started learning Rust and like how the compiler is fussy about things. My plan was to implement the data structures I knew, but I got stuck at the singly linked list's remove() method. I've read the book as well, but I have no clue how to simplify this further:
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Factor is faster than Zig
My impression from the article is that Zig provides several different hashtables and not all of them are broken in this way.
This reminds me of Aria's comment in her Rust tutorial https://rust-unofficial.github.io/too-many-lists/ about failing to kill LinkedList. One philosophy (and the one Rust chose) for a stdlib is that this is only where things should live when they're so commonly needed that essentially everybody needs them either directly or to talk about. So, HashTable is needed by so much otherwise unrelated software that qualifies, BloomFilter, while it's real useful for some people, not so much. Aria cleaned out Rust's set of standard library containers before Rust 1.0, trying to keep only those most people would need. LinkedList isn't a good general purpose data structure, but, it was too popular and Aria was not able to remove it.
Having multiple hash tables feels like a win (they're optimized for different purposes) but may cost too much in terms of the necessary testing to ensure they all hit the quality you want.
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Was Rust Worth It?
> Cyclic references can be dealt with runtime safety checks too - like Rc and Weak.
Indeed. Starting out with code sprinkled with Rc, Weak, RefCell, etc is perfectly fine and performance will probably not be worse than in any other safe languages. And if you do this, Rust is pretty close to those languages in ease of use for what are otherwise complex topics in Rust.
A good reference for different approaches is Learn Rust With Entirely Too Many Linked Lists https://rust-unofficial.github.io/too-many-lists/
- What are some of projects to start with for a beginner in rust but experienced in programming (ex: C++, Go, python) ?
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How to start learning a systems language
Second, once you've finished something introductory like The Book, read Learning Rust With Entirely Too Many Linked Lists. It really helped me to understand what ownership and borrowing actually mean in practical terms. If you don't mind paying for learning materials, a lot of people recommend Programming Rust, Second Edition by Blandy, Orendorff, and Tindall as either a complement, follow-up, or alternative to The Book.
- My team might work with Rust! But I need good article recommendations
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Conversion?
Learning Rust With Entirely Too Many Linked Lists which highlights a lot of the differences with how you need to structure your code in Rust compared to other languages.
What are some alternatives?
muzero-general - MuZero
rust - Empowering everyone to build reliable and efficient software.
PettingZoo - An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Rustlings - :crab: Small exercises to get you used to reading and writing Rust code!
gym - A toolkit for developing and comparing reinforcement learning algorithms.
book - The Rust Programming Language
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.
CppCoreGuidelines - The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++
gym-battleship - Battleship environment for reinforcement learning tasks
easy_rust - Rust explained using easy English
TexasHoldemSolverJava - A Java implemented Texas holdem and short deck Solver
x11rb - X11 bindings for the rust programming language, similar to xcb being the X11 C bindings