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A Machine-Learning Approach To Computer Go.pdf

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Preview of A Machine-Learning Approach to Computer Go
🔗 Source: web.archive.org
📊 Size: 399 KB
📄 Pages: 27 pages
⬇️ Downloads: 168

Summary

A machine-learning approach is proposed to play the game of Go, using a neural network to approximate a value function over the space of board states and temporal difference learning to refine it. The game of Go is extremely difficult for computers to play well due to its huge state space, large branching factor, difficulty in constructing a heuristic function, and need for a deep look-ahead. Traditional AI methods used in computer chess are not applicable to Go, making it necessary to develop alternative methods. The proposed approach shows promise, but its effectiveness is limited when used alone, and it may be more useful when combined with other move selection techniques.

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Description

A machine-learning approach is proposed to play the game of Go, using a neural network to approximate a value function over the space of board states and...

Technical Information

  • File Format: PDF
  • File Size: 399 KB
  • Pages: 27
  • Language: EN
  • Total Downloads: 168
  • Last Updated: 3 hours ago

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