unfinished experiment · 2025 · unfinished
Mortal Kombat Jax AI experiment
An unfinished screen-feedback controller for Jax Briggs in Mortal Kombat, usually tested against another Jax in practice mode. The owner recalls HP graphs, a live neural-network visualization, reward/penalty training, movement, attacks and special moves, and challenges by friends. It occasionally won; reliable performance was never established.
Evidence and limitations
Recovered source includes a PPO CnnPolicy variant: screen frames and calibrated HP regions feed gameplay observations; damage deltas reward opponent damage and penalize own damage; actions drive keyboard input. Visualization code exposes both HP values and a neural diagram. Checkpoints and session logs survive, but sampled HP fields are zero and one log entry repeats. They do not establish win rates or a validated training outcome. Older variants also exist; the exact version used in remembered sessions is unverified. The narrative of practice fights and friends challenging it is owner-reported. No raw checkpoints, logs or game imagery are published.
Technologies
Python, OpenCV, PyTorch, Gymnasium, Stable-Baselines3 PPO, Tkinter
Separate fighting experiments
Proposed only: compare direct game-state input with screen-only observations in a common browser fighting environment under controlled, reproducible evaluation. Game choice, controller details and feasibility remain unresolved. No integration or comparison results exist.
Read the separate Flyweight project