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angelfish

Some exercise implementations of chess engines using the very nice sunfish framework and tools

mlearn branch

  • The branch holds experiments of reinforcement learning.
  • The main goal of angelfish project.

Engines implemented

In order of increasing performance:

  • Minimax
  • Negamax
  • AlphaBeta - with pruning, transposition table and iterative deepening
  • Sunfish - refitting as a mixin

All engines have a method search(pos,secs) as in class sunfish.Search

Framework

  • Decouple sunfish.Position into move handlings and score evaluations separately
    • Subclass sunfish.Position as Superposition to handle moves,
      • moves generation
      • game over test (test "k" in board instead of score > sunfish.MATE_LOWER)
      • legal test
      • retain sunfish convention of black player moves from a rotated position
    • A new SunfishPolicy class to handle heuristic evaluation of position in engines
      • abstraction of sunfish.Position.score and sunfish.Position.value
      • the base class adopted sunfish.pst scores

A screenshot

screenshot

python3 only, or pypy3

git cloning with a submodule

  • sunfish is imported into angelfish.engines as a git submodule
  • My forked sunfish in a separate branch has added __init__.py to make sunfish importable
git clone --recursive https://github.com/VC-H/angelfish.git

angelfish

  • Distant relatives of sunfish
  • Refer to a class of fresh water aquarium fish for appreciation