while working on an idea to create a simple (think it's going to be simple) AI project I was wondering what kind of datastructures would apply better. The project's goals are the following:
agents will just wander around doing uninformed searches trying to get to know the map
we tell those agents to go somewhere in the map. They will use an informed search if possible (if they know howto get there) and an uninformed search if they don't really know how to go there.
the map will probably be represented in 2d to keep things simpler. In an initial state a square is either walkable or unwalkable. Later the project could evolve so squares could be walkable, walkable in only on direction or unwalkable.
agents will have differences so they don't work in the same way in the map - an agent could search using algorithm X and the other algorithm Y wich would give them different results. Other "traits" could influence their movement.
Now the purpose of this post if to get some suggetionss regarding wich datastructures and algorithms to use.
Here's what needs to be represented:
-> general map, used to draw to screen and as the source where the agents will move while trying to find out stuff regarding
-> map (of known paths) for each agent
Also, another question:
if agents receive "orders" can they still be considered autonomous?