I Can Jump! Exploring Search Algorithms for Simulating Platformer Players

Platformer games let players solve real-time, physics-based puzzles by jumping and moving around to reach different goals. Designing levels for this context is a non-trivial task; the placement of well-timed jumps, moving platforms, interesting traps, etc., has a complex relationship to in-game challenge and the existence of possible solutions. In this work, we describe three different search algorithms (A, MCTS and RRT) that could be used to simulate player behaviour in the platformer domain. We evaluate and compare the three approaches applied to three non-trivial levels, showing a possible iterative workflow of use to designers, and research progress in designing search algorithms for platformer