Some topics (google them):

- moving in a game world: navigation mesh, waypoints, pathfinding (A star/A*)

- decision making: eg. behavior trees

- steering in a game world (avoiding obstancle on the path, moving in a group): steering behavior

- general AI programming: usage of scripting

- reacting to the environment: scanning the surrounding, triggering agents

Keep away from:

- neural networks (commonly not really useful for game AI)

- genetic algorthm (either not really useful for game AI)

PS: visit the GDC vault and check out all the presentations of AI to get an idea about what is needed and what to avoid ;-)

Thanks, earlier I wanted to work on learning NPCs

Hmm... are we talking about the same thing ? I mean NonPlayerCharacter...

Also, should I learn to work with engines like Unity?

It could be an easy way to represent your work (check out Unreal4 too), thought you don't need fancy art. A few moving boxes to represent a crowd AI is better than to spend days to get an animated character into your engine. Test it out, but remember that you want to show off AI and not a game.

If you haven't worked with AI before, don't expect to be up and running in days, weeks, or even months. It is a very complicated area. Which does beg the question... why would you chose to start your MS on something that you readily admit you have no knowledge of? A better question would probably be, "why do you want to work on learning AI? What is it you hope to accomplish, prove, solve, improve, etc?"

Be that as it may, there are many billions of reasons why learning AI is not used in games (at least not a lot). A simple search through this forum will provide you with spirited commentary on the subject. However, you do not even want to delve into the topic of learning AI until you know how to make static, authored AI. That's somewhat like saying, "I don't know how to do arithmetic but I heard that differential calculus was cool... how do I start with differential calculus?"

That said, there is a book list stickied at the top of this forum. That will get you started with the basics.

Unless you plan on doing something very novel, I'm not really aware of any game-style AI that would be even slightly interesting as a master's thesis. Game AIs and classical AIs are different beasts. AIs that learn to play games are a different matter, but doesn't sound like what you're doing.

Have you met with your adviser yet to discuss your thesis proposal?

Both of those books are good, but in different ways. Mat Buckland's "... by Example" book is going to give you a better understanding of things you will use directly in game AI. (Same with Millington's.)

The techniques that are going to give you the most mileage in game AI are:

• State Machines
• Behavior Trees
• A* Pathfinding
• Steering
• Utility systems

Other things such as influence maps, etc. will augment that, but they aren't as necessary.