Reconnaissance Blind Chess

  • Developed an efficient Deep Learning pipeline utilising a Recurrent Neural Network and Diffusion-based Generator to reconstruct the state-space from histories.
  • Addressed the Blind Chess problem, a variant of chess where players lack awareness of the pieces’ locations, and proposed a Reinforcement Learning pipeline for optimal policy exploration using state-of-the-art techniques.

Code | Report