DI-star Alternatives

DI-star reviews and mentions

• Better AI ?
  1 project | /r/allthingszerg | 28 Dec 2022

  There is an AI/bot scene for SC2, I don't have many links but you can start by looking here: https://github.com/opendilab/DI-star https://www.youtube.com/watch?v=fvQF-24IpXs (Harstem and uThermal both have more videos vs different bots).

• [ENG] 2022 GSL S3 Code S RO.20 Group B
  1 project | /r/starcraft | 29 Aug 2022
• Any idea about DI-star ？ It's an AI model could beat top human players in StarCraft II!
  1 project | /r/reinforcementlearning | 13 Jun 2022

  Looks like a simplified AlphaStar using LSTM RNN instead of Pointer Transformer, much heavier supervised imitation learning, Zerg vs Zerg only (with simplified build order module), and a much smaller AlphaStar League: https://github.com/opendilab/DI-star/blob/main/docs/guidance_to_small_scale_training.md

  1 project | /r/starcraft | 13 Jun 2022

  For more information，plz visit out GitHub page：https://github.com/opendilab/DI-star

• Any idea about DI-star？An AI model could beat top human players in StarCraftII
  1 project | news.ycombinator.com | 13 Jun 2022
• A large-scale game AI distributed training platform developed for StarCraftII
  1 project | news.ycombinator.com | 22 May 2022
• Why can't we make a perfect AI for Starcraft through evolution
  1 project | /r/reinforcementlearning | 23 Apr 2022

  First of all, let's discuss what the level of AI is now. If the "level" refers to the capability of competing, the current AI has been very closed to the top human player in some types of games, like chess, Texas Poker, and Mahjong of CARDS, DOTA2 of MOBA, as well as StarCraft2 of RTS. As for other games, if we have enough human resources and computing performance, we also can get similar results. If the "level" has other meanings, like AI agents having human behavior, intelligent NPC can be designed specifically for different people so that they can have different gaming experience. These are all at the stage of issue-defining and exploring new technology solutions. Although traditional game AI is mostly based on hard code, it still has much prior knowledge. In recent years, some hot ML-related techs have performed well in competitiveness while in other fields, they haven't found the perfect entry point. If we expand the conclusions above in detail, the design of game AI can be divided into two parts: issue defining and issue solving. For those competitive issues which have already got complete definitions, their core issue is to explore the optimal strategy based on the evaluation standard, like ladder points. Traditional solutions can deal with less complex scenarios, like chess and Gobang. While machine learning related techs, including deep learning and reinforcement learning, they can perform very well in much more complex games, like StarCraft II. {For this you can try it in DI-star: this project is a reimplementation (with a few improvements) of Alphastar (Only Zerg vs Zerg) based on OpenDILab.}

• Show HN: Come and fight professional AI in StarCraftII
  1 project | news.ycombinator.com | 14 Apr 2022
• DI-Star (Starcraft 2 AI, Continuation of AlphaStar)
  1 project | news.ycombinator.com | 11 Apr 2022
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