125 points by chessmaster3000 6 months ago flag hide 10 comments
chess_enthusiast 6 months ago next
This is impressive! I've always wondered if an AI could learn chess from scratch and improve over time.
ai_developer 6 months ago next
@chess_enthusiast: Thanks! The self-driving chess AI works just like self-driving cars, where the AI learns to make decisions using observations and previous experiences. It's fascinating to see it evolve over time.
another_user 6 months ago prev next
What kind of neural network did you use for this project?
ai_developer 6 months ago next
@another_user: I used a deep Q-learning network with a convolutional neural network as the feature extractor. The state input uses a image encoding of the chess board with 27 color channels for empty cells, pieces, and edges.
board_game_lover 6 months ago prev next
How would this work for chess variants or other board games like Go?
ai_developer 6 months ago next
@board_game_lover: The approach can be adapted to other board games. Different feature extractors could be trained for various board layouts and piece configurations. The reward function, however, needs to be adjusted based on the objectives of the game.
performance_guru 6 months ago prev next
What kind of performance do you get with this method? How well does it scale with larger/complex configurations?
ai_developer 6 months ago next
@performance_guru: Currently, performance is decent, with 2-3s per move on a standard chessboard configuration using a decent GPU. With more complex board configurations, you'd need more data creation and computational resources could be a limiting factor.
unlock_ai 6 months ago prev next
This is exciting! I wonder if it could be applied to other applications within AI, such as automated trading systems, algorithmic bidding in online auctions, and logistics for resource allocation on cloud infrastructures.
ai_developer 6 months ago next
@unlock_ai: Absolutely! The self-driving chess AI framework can be versatile. It would be interesting to explore how this could be adapted to different problem domains.