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GAME AI
Class
CS380
Instructor
iIker Silvano
Languages
C++ and DirectX 9
About
In this class, we learned multiple things about AI in games. We learned things that were used years ago in some games and how things evolved until now. Here you have some of the worth to mention techniques that were implemented in an already working framework.
Pathfinding : A*
After learning and implementing Dijkstra, we learned how A* was incredibly faster. However, although a local optimal solution is found, it is not ensured to be the global optimal solution, which is why we added a parameter to change the heuristics and how the distance is measured to be able to get a variety of results.
Pathfinding : JPS+
After learning A*, the teacher showed the slides of JPS+ and included it as an extra objective in an assignment. After implementing it we can see how the visited nodes amount is considerably smaller and how it is way faster than A*.
Field Analysis
One of the most recurrent problems in game development is how an enemy can see the player and how it should pursue it. We do this by using some techniques of field analysis to give hints to the enemy of where should it check for the player and what should it do after losing track of the player. The pathfinding and field analysis techniques were used to create a hide and seek game.
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