policy

BetaZero

YamArtur · PyTorch

or hover any field below to flag it

Overview

Name
BetaZero
Author
YamArtur
Framework
PyTorch
License
MIT
Skill type
other
Evidence level
untested
Task description
BetaZero is an AlphaZero-inspired chess system: a PyTorch policy–value CNN trained by self-play with MCTS, producing move probabilities and position value. It reads a board via an Arduino-driven 8×8 LDR sensor matrix and commands a servo robotic arm to play the selected moves end-to-end. Includes pe

Spaces

Action space
other · 0-dim · 0Hz
Observation space
  • type: other

Links

HuggingFace repo
null
Paper (arXiv)
null

Compatible robots

3+17 mentioned but not in catalog yet

Compatible environments

0

No environments list BetaZero yet.

Datasets that reference this policy

0

No datasets reference BetaZero yet.