If you're looking to research and learn about pathfinding in general, I'd definitely suggest learning more than just one algorithm. You'll want to understand the overall concepts but be able to apply them to whatever it is you are working on. Most game developers who need to do any serious pathfinding end up writing their own custom algorithms, although highly based on known solutions, every game is different and will have different requirements.

I'd start by reading up on some of the more well know methods like A*, Dijkstra's Algorithm, Depth and Breadth-First searches. There's a lot of good information on the internet on each of these. (http://en.wikipedia.org/wiki/Pathfinding)

While reading them, take note on what the upsides and downsides are to each approach, as well as the type of data the algorithm can operate on. Can it be applied to 3-dimensional paths? Can it be modified to account for our human AI who wants to avoid the landmines in the map?

When it comes to pathfinding, A* is pretty much the golden ticket that everyone uses. You should definitely know how it works. (http://en.wikipedia.org/wiki/A*_search_algorithm)

Here's a good example of A* as it applies to RTS game, which need to take entities of different size into account: http://aigamedev.com/open/tutorials/clearance-based-pathfinding/

Good luck!

If you're looking to research and learn about pathfinding in general, I'd definitely suggest learning more than just one algorithm. You'll want to understand the overall concepts but be able to apply them to whatever it is you are working on. Most game developers who need to do any serious pathfinding end up writing their own custom algorithms, although highly based on known solutions, every game is different and will have different requirements.

I'd start by reading up on some of the more well know methods like A*, Dijkstra's Algorithm, Depth and Breadth-First searches. There's a lot of good information on the internet on each of these. (http://en.wikipedia.org/wiki/Pathfinding)

While reading them, take note on what the upsides and downsides are to each approach, as well as the type of data the algorithm can operate on. Can it be applied to 3-dimensional paths? Can it be modified to account for our human AI who wants to avoid the landmines in the map?

When it comes to pathfinding, A* is pretty much the golden ticket that everyone uses. You should definitely know how it works. (http://en.wikipedia.org/wiki/A*_search_algorithm)

Here's a good example of A* as it applies to an RTS game, which needs to take entities of different size into account: http://aigamedev.com/open/tutorials/clearance-based-pathfinding/

Good luck!

If you're looking to research and learn about pathfinding in general, I'd definitely suggest learning more than just one algorithm. You'll want to understand the overall concepts but be able to apply them to whatever it is you are working on. Most game developers who need to do any serious pathfinding end up writing their own custom algorithms, although highly based on known solutions, every game is different and will have different requirements.

I'd start by reading up on some of the more well know methods like A*, Dijkstra's Algorithm, Depth and Breadth-First searches. There's a lot of good information on the internet on each of these. (http://en.wikipedia.org/wiki/Pathfinding)

While reading them, take note on what the upsides and downsides are to each approach, as well as the type of data the algorithm can operate on. Can it be applied to 3-dimensional paths? Can it be modified to account for our human AI who wants to avoid the landmines in the map?

When it comes to pathfinding, A* is pretty much the golden ticket that everyone uses. You should definitely know how it works. (http://en.wikipedia.org/wiki/A*_search_algorithm)

Here's a good example of A* as it applies to RTS game, which need to take entities of different size into account: http://aigamedev.com/open/tutorials/clearance-based-pathfinding/

Good luck!

If you're looking to research and learn about pathfinding in general, I'd definitely suggest learning more than just one algorithm. You'll want to understand the overall concepts but be able to apply them to whatever it is you are working on. Most game developers who need to do any serious pathfinding end up writing their own custom algorithms, although highly based on known solutions, every game is different and will have different requirements.

I'd start by reading up on some of the more well know methods like A*, Dijkstra's Algorithm, Depth and Breadth-First searches. There's a lot of good information on the internet on each of these. (http://en.wikipedia.org/wiki/Pathfinding)

While reading them, take note on what the upsides and downsides are to each approach, as well as the type of data the algorithm can operate on. Can it be applied to 3-dimensional paths? Can it be modified to account for our human AI who wants to avoid the landmines in the map?

When it comes to pathfinding, A* is pretty much the golden ticket that everyone uses. You should definitely know how it works. (http://en.wikipedia.org/wiki/A*_search_algorithm)

Here's a good example of A* as it applies to RTS game, which need to take entities of different size into account: http://aigamedev.com/open/tutorials/clearance-based-pathfinding/

Good luck!