Add some basic knowledge of 'planners'. The utility of that is for more complex NPC tasks that have multiple solutions in a more complex environment and for which decisions have to be made prioritizing what to do when/where (and handling tasks that get interrupted/retried/abandoneded or reactions to a changing situation).

Its higher level AI built ontop of the more basic mechanisms/methods

no, I haven't met my adviser yet (I'll visit him this week), also in our university no one has worked game AI, and that's scary!

From a game perspective, you only need "something reasonably behaving", and "looking good". If that can be done with eg a hard-coded solution, that'd be fine.

From an academic perspective, a hard-coded solution is not relevant (unless you have a scientific method to derive that solution!). Also "looking good" is probably less relevant. On the other hand, the fundamental approach that you use is probably much more relevant.

Your goal is not to make an AI/NPC. Your goal is to find and describe a novel solution to the AI/NPC creation problem. You illustrate it with an example AI/NPC to show it actually works. There is a subtle yet important shift in focus here!

Add some basic knowledge of 'planners'. The utility of that is for more complex NPC tasks that have multiple solutions in a more complex environment and for which decisions have to be made prioritizing what to do when/where (and handling tasks that get interrupted/retried/abandoneded or reactions to a changing situation).

Its higher level AI built ontop of the more basic mechanisms/methods

Thank you I'll look into that.

no, I haven't met my adviser yet (I'll visit him this week), also in our university no one has worked game AI, and that's scary!

From a game perspective, you only need "something reasonably behaving", and "looking good". If that can be done with eg a hard-coded solution, that'd be fine.

From an academic perspective, a hard-coded solution is not relevant (unless you have a scientific method to derive that solution!). Also "looking good" is probably less relevant. On the other hand, the fundamental approach that you use is probably much more relevant.

Your goal is not to make an AI/NPC. Your goal is to find and describe a novel solution to the AI/NPC creation problem. You illustrate it with an example AI/NPC to show it actually works. There is a subtle yet important shift in focus here!

WOW, I didn't know that

Also, if I want to apply for a good university for phD in future, my work must be more scientific? (I wanted to apply for MS, but I stayed here because of some reasons).

Thank you

It all a matter of pleasing the public.

If you make a game (especially commercially), you have to please the players. Most players are not at home with AI techniques, depending on the AI character and the game, they may even hardly notice its existance. So the main goal is to make something that doesn't stand out as "it acts weird".

If you write a thesis, the public is your supervisor. His/her interest is in the science that you use to solve the problem. If it looks good, that's nice too, but likely not the main thing you are graded on (but you should of course discuss this with your supervisor, if only to avoid nasty surprises!)

Now if you look at AI techniques as listed here, you're looking at solutions in the game case, as everybody in this forum does "games" in one way or another.

Those techniques are designed to work in the practical cases that you encounter for your average game. Those techniques are "use any means you can to show the player what he expects". If the shortest way is "cheating", eg by hard-coding a solution, great! Problem solved, let's move on to the next item on the todo list.

The scientific approach is not about getting to the end of the todo list before the deadline or about fooling players enough that they buy it. It's about investigating the proper way (which can mean lots of different things, ask your supervisor) to create an AI.

Edit: So the things listed here in the topic are definitely interesting to study, it gives you a wider view of the topic, which is never bad. You may even find a way to combine the scientific solution, and a technique listed here, who knows!

As for steps in the future, not sure. The topic and the solution is probably just one of the things they will look at. You as person is just as important is my guess, if not more (but I don't know for sure).

It all a matter of pleasing the public...

Thank you so much for advice

"or about fooling players enough that they buy it"

But consider the definition of the Turing Test ...

Add some basic knowledge of 'planners'.

Thanks, W... knew I forgot something.

Also, read my article that I wrote for GDMag a while back. It's on my web site now.

http://intrinsicalgorithm.com/IAonAI/2012/11/ai-architectures-a-culinary-guide-gdmag-article/

Add some basic knowledge of 'planners'.

Thanks, W... knew I forgot something.

Also, read my article that I wrote for GDMag a while back. It's on my web site now.

http://intrinsicalgorithm.com/IAonAI/2012/11/ai-architectures-a-culinary-guide-gdmag-article/

Thanks again

Another aspect that you might want to touch on is 'uncertainty', as in how an AI can be made to handle imperfect/incomplete data or unpredictable behaviors in the environment. The basic tools like planners and pathfinding searches become trivial compared to trying to build the judgement and metrics used to figure when something (in a specific environment) is good enough (instead of mathematically optimal).

This part of AI is where it becomes magnitudes harder (extending into 'learning' if it is done while the game is running, versus being preformulated).

Another aspect that you might want to touch on is 'uncertainty', as in how an AI can be made to handle imperfect/incomplete data or unpredictable behaviors in the environment. The basic tools like planners and pathfinding searches become trivial compared to trying to build the judgement and metrics used to figure when something (in a specific environment) is good enough (instead of mathematically optimal).

This part of AI is where it becomes magnitudes harder (extending into 'learning' if it is done while the game is running, versus being preformulated).

Thanks you :)