Exploration in NetHack With Secret Discovery
  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.
