Learning to play from what it can see.

A local game-playing AI research project built around pixels, bounded actions, and replay.

The idea

The current work uses a controlled training world to study navigation and recovery. Each move starts from a visible observation and ends with a fresh check of what happened.

What it explores

Pixel-based observations
Small actions with stop and recovery behavior
Recorded traces for reviewing progress