Do graph search algorithms have applications for strategy? https://www.redblobgames.com/pathfinding/a-star/introduction... Consider a game like age of empires. The cost of attacking a village goes up when a wall is built around it. But when canon are invented, the cost goes down.
Can we model each map (before and after invention of canon) and use it to plan a strategy?
Same for building a port , portal or airport.
I would guess it's probably not worth it because "how much do cannons improve my overall position" is a tricky question, and making a really intelligent and sophisticated answer is not really visibly distinct to players from a stupid heuristic like a sigmoid function of how many walls the player has built. It's an amusing curiosity that you can build stupid walls and trick the AI into researching the tech, but it's better to make those walls you're paying for useful, so you can rely on that being generally true.
I think a lot about some advice I heard from the creator of Brogue. Essentially players have a tough time figuring out how AIs make their decisions and often assign complex motives to them when they don't exist. His example was he coded archers to try to maintain a position in some range band from the player as their primary motivation in a vacuum. The community would assign all sorts of supposed logic to archer behavior because in real-world environments with extra geometry or extra situational AI routines they couldn't see behind the curtain. Additionally, that most game AI exists to create a fun experience for the player, we only make it try to play well in service of that goal.
I agree, it seems tricky to actually quantify. The hard part is to create the graph in the first place, before you start the graph search.
There must be methods for creating simplified approximations.
