Timo Bertram, Johannes Furnkranz, And Martin Muller, "Supervised And Reinforcement Learning From Observations In Reconnaissance.pdf

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Preview of Timo Bertram, Johannes Furnkranz, and Martin Muller, "Supervised and Reinforcement Learning from Observations in Reconnaissance
🔗 Source: ieee-cog.org
📊 Size: 194 KB
📄 Pages: 4 pages
⬇️ Downloads: 119

Summary

Researchers adapted an AlphaGo-inspired approach to play Reconnaissance Blind Chess, an imperfect information game, by training a supervised agent on game records and then improving it through self-play with Proximal Policy Optimization, achieving an ELO of 1330 without using search or making assumptions about the true game state.

Description

Researchers adapted an AlphaGo-inspired approach to play Reconnaissance Blind Chess, an imperfect information game, by training a supervised agent on game...

Technical Information

  • File Format: PDF
  • File Size: 194 KB
  • Pages: 4
  • Language: EN
  • Total Downloads: 119
  • Last Updated: 2 months ago

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