human-like

Trained transformer-based chess models for rating buckets from 800 to 2500+, predicting moves, thinking time, and outcome. Achieves strong accuracy with only 9M parameters, and includes a novel thinking-time prediction component.

Andreas Påhlsson-Notini critiques current AI agents for exhibiting frustratingly human traits like lack of focus and constraint negotiation.