mlsanityData to 7 Oct 2026

LiteEFG: An Efficient Python Library for Solving Extensive-form Games

arXiv 2407.20351 ↗First posted 29 Jul 2024cs.GT cs.AI cs.LGcited by 3

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Abstract (arXiv)

LiteEFG is an efficient library with easy-to-use Python bindings, which can solve multiplayer extensive-form games (EFGs). LiteEFG enables the user to express computation graphs in Python to define updates on the game tree structure. The graph is then executed by the C++ backend, leading to significant speedups compared to running the algorithm in Python. Moreover, in LiteEFG, the user needs to only specify the computation graph of the update rule in a decision node of the game, and LiteEFG will automatically distribute the update rule to each decision node and handle the structure of the imperfect-information game.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 11 of its 20 references that are in the map. First posted on arXiv 29 Jul 2024.

Builds on

11 of 20 references.

References · 11

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2013Playing Atari with Deep Reinforcement Learningcited by 3,211
  3. 2019Dota 2 with Large Scale Deep Reinforcement Learningcited by 1,084
  4. 2019The Hanabi Challenge: A New Frontier for AI Researchcited by 194
  5. 2019OpenSpiel: A Framework for Reinforcement Learning in Gamescited by 180
  6. 2018Solving Imperfect-Information Games via Discounted Regret Minimizationcited by 68
  7. 2022A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Gamescited by 64
  8. 2020Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descentcited by 56
  9. 2021Last-iterate Convergence in Extensive-Form Gamescited by 27
  10. 2022The Power of Regularization in Solving Extensive-Form Gamescited by 21
  11. 2022Alternating Mirror Descent for Constrained Min-Max Gamescited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025Scale-Invariant Regret Matching and Online Learning with Optimal Convergence: Bridging Theory and Practice in Zero-Sum Gamescited by 3
  2. 2026Game of Thought: Robust Information Seeking with Large Language Models Using Game Theorycited by 1
  3. 2026Decision Making under Imperfect Recall: Algorithms and Benchmarkscited by 0