Furthermore, denote the cost of visiting a room \(v \in V \) with \(C(v)\). To facilitate algorithm’s presentation let’s now make some assumptions, simplifications, and definitions.ĭenote the set of all rooms with \(V\) and set of all corridors with \(E\). This kind of dungeon goal and map posed as an attributed graph, motivated me to come up with an algorithm that calculates the optimal path for the team. The large boxes are rooms whereas the sequences of small boxes represent the corridors. In addition, for the same reason player should rather avoid redundant room visits as they do not contribute to the progress towards the goal.Īn example map with various event annotations. Such events in rooms and corridors are marked on the dungeon maps.įor this reason, in this kind of dungeon campaigns, it is almost always a good idea to explore only 90% of the rooms and not more than that. Fighters suffer stress penalty, traps deal HP damage, and resources such as light deplete with each step team takes. Visiting rooms or corridors is always a costly decision in the game by design. The connections, and therefore the structure of the dungeon map, could be quite arbitrary. Every room is connected to one or more other rooms with corridors. Dungeon maps are designed as a network of rooms. One of the common goals in dungeons is, namely, Explore 90% of the rooms. I really enjoy playing this game as in it’s essence, it pushes the player to develop efficient combat, exploration and team formation strategies under numerous constraints introduced by game dynamics. Every dungeon campaign has a goal, and the player suffers a big penalty when returned back from the dungeon without achieving the goal. The player gathers a gang of fighters with various characteristics and skills and goes onto exploration of dungeons with various properties. Recently I have been playing this game called Darkest Dungeon.
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