awesome-game-ai
★ 964
vs
on-policy
★ 2.0k
awesome-game-ai vs on-policy
awesome-game-ai: This repository is a curated list of resources for game AI, specifically focusing on multi-agent learning in both perfect and imperfect information games. It includes open-source projects, research papers, conferences, and competitions for various popular games.; on-policy: This repository implements MAPPO, a multi-agent variant of PPO, widely used in cooperative multi-agent games and research. It provides robust implementations for various multi-agent environments like StarCraft II, Hanabi, and Google Research Football, along with detailed training scripts and hyperparameter guidance.
01
TL;DR
Choose awesome-game-ai if…Researchers exploring multi-agent reinforcement learning and game theory applications.
Choose on-policy if…Research and experimentation in cooperative multi-agent reinforcement learning
02
Side-by-Side Comparison
03
Features
awesome-game-ai01Curated list of multi-agent game AI resources.
02Coverage of perfect and imperfect information games.
03Links to open-source projects for various games (e.g., Chess, Go, Poker).
04Collection of seminal research papers categorized by game.
05Directory of relevant conferences, workshops, and competitions.
on-policy01Implementation of MAPPO (Multi-Agent PPO)
02Support for diverse multi-agent environments (e.g., StarCraft II, Hanabi)
03Ready-to-use training scripts for various scenarios
04Detailed hyperparameter guidance and updated results
05Default support for shared policy among agents
04
Use Cases
awesome-game-ai↳Researchers exploring multi-agent reinforcement learning and game theory applications.
↳Developers seeking open-source game AI projects or toolkits for implementation.
↳Academics and students studying advanced game AI concepts and historical breakthroughs.
on-policy↳Research and experimentation in cooperative multi-agent reinforcement learning
↳Benchmarking and evaluating PPO's effectiveness in MARL scenarios
↳Training AI agents for popular multi-agent games like StarCraft II and Hanabi
05
Best For
awesome-game-aiTrending
on-policyTrendingReinforcement LearningMulti-Agent AI
FAQ
FAQ
What is the difference between awesome-game-ai and on-policy?
Both awesome-game-ai and on-policy are in the RAG / Knowledge Base category. awesome-game-ai has 964 stars, while on-policy has 2.0k stars.
Which is better, awesome-game-ai or on-policy?
The best choice depends on your use case. Choose awesome-game-ai if Researchers exploring multi-agent reinforcement learning and game theory applications., and on-policy if Research and experimentation in cooperative multi-agent reinforcement learning.
Is awesome-game-ai free or open source?
Yes, awesome-game-ai is open source on GitHub.
Is on-policy free or open source?
Yes, on-policy is open source on GitHub (MIT).
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