Go-Explore Complex 3-D Game Environments for Automated Reachability Testing

Modern AAA video games feature huge game levels and maps, which are increasingly hard for level testers to cover exhaustively. As a result, games often ship with catastrophic bugs, such as the player falling through the floor or being stuck in walls. We propose an approach specifically targeted at reachability bugs in simulated 3-D environments based on the powerful exploration algorithm, Go-Explore, which saves unique checkpoints across the map and then identifies promising ones to explore from. We show that when coupled with simple heuristics derived from the game's navigation mesh, Go-Explore finds challenging bugs and comprehensively explores complex environments without the need for human demonstration or knowledge of the game dynamics. Go-Explore vastly outperforms more complicated baselines including reinforcement learning with intrinsic curiosity in both covering the navigation mesh and number of unique positions across the map discovered. Finally, due to our use of parallel agents, our algorithm can fully cover a vast 1.5 km × 1.5 km game world within 10 h on a single machine making it extremely promising for continuous testing suites.