
A New Complexity Scorecard for Game World Models
The paper proposes Transition Complexity Profile (TCP), a reproducible framework for measuring how difficult game-world transition prediction is at a specified interface. It evaluates branching, interaction-driven uncertainty, opponent influence, and temporal or spatial dependencies to improve comparisons across game-modeling and reinforcement-learning benchmarks.

