Why is Reinforcement Learning so rarely used in pathfinding?
- by doug
The venerable shortest-path graph theoretic algorithm A* and subsequent improvements (e.g., Hierarchical Annotated A*) is clearly the technique of choice for pathfinding in game development.
Instead, it just seems to me that RL is a more natural paradigm to move a character around a game space.
And yet I'm not aware of a single game developer who has implemented a Reinforcement Learning-based pathfinding engine. (I don't infer from this that the application of RL in pathfinding is 0, just that it's very small relative to A* and friends.)
Whatever the reason, it's not because these developers are unaware of RL, as evidenced by the fact that RL is frequently used elsewhere in the game engine.
This question is not a pretext for offering an opinion on RL in pathfinding; in fact, i am assuming that the tacit preference for A* et al. over RL is correct--but that preference is not obviously to me and i'm very curious about the reason for it, particularly from anyone who has tried to use RL for pathfinding.
