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 deep synoptic monte-carlo planning

Deep Synoptic Monte-Carlo Planning in Reconnaissance Blind Chess

Neural Information Processing Systems

This paper introduces deep synoptic Monte Carlo planning (DSMCP) for large imperfect information games. The algorithm constructs a belief state with an unweighted particle filter and plans via playouts that start at samples drawn from the belief state.

  deep synoptic monte-carlo planning, name change, reconnaissance blind chess, (6 more...)
  Industry: Leisure & Entertainment > Games > Chess (0.49)
  Technology: Information Technology > Artificial Intelligence > Representation & Reasoning (0.92)

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Deep Synoptic Monte-Carlo Planning in Reconnaissance Blind Chess

Neural Information Processing Systems

DSMCP is the basis of the program Penumbra, which won the official 2020 reconnaissance blind chess competition versus 33 other programs. This paper also evaluates algorithm variants that incorporate caution, paranoia, and a novel bandit algorithm. Furthermore, it audits the synopsis features used in Penumbra with per-bit saliency statistics.

  belief state, deep synoptic monte-carlo planning, reconnaissance blind chess, (3 more...)
  Industry: Leisure & Entertainment > Games > Chess (0.69)
  Technology: Information Technology > Artificial Intelligence > Representation & Reasoning > Planning & Scheduling (0.49)

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