Exploration in NetHack With Secret Discovery
This work addresses exploration automation for players in roguelike games, offering incremental improvements over prior methods.
The paper tackled the problem of efficient exploration in roguelike games like NetHack, where incomplete information such as secret doors poses challenges, and showed that their algorithm based on occupancy maps significantly reduces exploration time compared to greedy approaches and existing automated players.
Roguelike games generally feature exploration problems as a critical, yet often repetitive element of gameplay. Automated approaches, however, face challenges in terms of optimality, as well as due to incomplete information, such as from the presence of secret doors. This paper presents an algorithmic approach to exploration of roguelike dungeon environments. Our design aims to minimize exploration time, balancing coverage and discovery of secret areas with resource cost. Our algorithm is based on the concept of occupancy maps popular in robotics, adapted to encourage efficient discovery of secret access points. Through extensive experimentation on NetHack maps we show that this technique is significantly more efficient than simpler greedy approaches and an existing automated player. We further investigate optimized parameterization for the algorithm through a comprehensive data analysis. These results point towards better automation for players as well as heuristics applicable to fully automated gameplay.