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Show HN: My AI-powered Chess Engine Outperforms Stockfish(github.io)

334 points by chess_wizard 1 year ago | flag | hide | 15 comments

  • chessmaster 1 year ago | next

    Fantastic work! I remember when I built my first chess engine, it couldn't even beat a beginner. Outperforming Stockfish in complex positions is a real testament to your AI capabilities. Good job and make more people aware of it!

    • usertwo 1 year ago | next

      @chessmaster <3

  • curious 1 year ago | prev | next

    How did you manage to create an engine capable of such performance in beating Stockfish? I can imagine the countless hours you spent fine-tuning algorithms and models. Any pointers on to where to begin?

    • creator 1 year ago | next

      Lots of research, experimentation, and perseverance. Combining traditional chess algorithms, Monte Carlo Tree Search and neural networks really paid off in the end. If you are new to AI chess engines, start by reading the AlphaZero paper and implementing an 8-puzzle solver.

      • ai_enthusiast 1 year ago | next

        The idea of combining multiple approaches to achieve this sounds innovative. I have heard about using neural networks for these tasks, but real-world application pointers are priceless. Thank you!

        • curious 1 year ago | next

          @ai_enthusiast, do you know any repositories or resources that dive deep into combining neural networks and traditional chess algorithms?

          • reference_link 1 year ago | next

            [Chess AI resources](https://www.example.com/chess-ai-resources) the paper you're looking for, @curious

            • curious 1 year ago | next

              @reference_link, you are a lifesaver! Thanks for sharing this. This is precisely what I was looking for.

  • deeplearner 1 year ago | prev | next

    I've been working on a chess engine with my own deep reinforcement learning approach. Currently, it can only beat Fruit 2.1, but it's always exciting to have new inspirations. Thanks for sharing!

    • thirdparty 1 year ago | next

      You're on the right track with DRL, but you might find it useful to read up on the Human-Level Control Through Deep Reinforcement Learning Paper. The insights on how the AI developed chess and shogi playing abilities could boost your project.

      • creatorthree 1 year ago | next

        @thirdparty, thank you for the reference! I will read through this. I am confident this would provide a leap in my AI research.

  • anonymous 1 year ago | prev | next

    Impressive. You should also consider porting this engine to a web version or app for users to check out. Engaging users in trying your creation increases exposure and contributions to your work.

    • noplan 1 year ago | next

      I dont like chess :/ kappa

  • knowledgable 1 year ago | prev | next

    Outstanding. If you are planning to share your source code or any chess puzzles solved by your model for the community, consider releasing it under open-source permissive licenses.

  • blespok 1 year ago | prev | next

    This is the kind of innovation we need to speed AI research in gaming problems. Great work! And thank you for sharing the open-source links. I'm excited to see the impact of your project.