The most common question I get asked by students is not what is artificial intelligence, but what is
the difference between artificial intelligence and machine learning?
As there are many common misconceptions that the terms are interchangeable.
However, they are not.
And in order to understand the differences, we really need to take a look at what artificial intelligence
is.
In a nutshell, artificial intelligence is the intelligence demonstrated by machines, whereas natural
intelligence would be that possessed by most living creatures.
The field of AI became an academic discipline in 1956.
The traditional types of problems that I worked on were the replication of the human abilities of reasoning,
knowledge, representation, planning, learning, natural language processing perception and the ability
to manipulate objects.
When it comes down to it, AI is really all about having a machine learn to adapt to new situations.
However, doing this currently with a holistic approach is somewhat daunting, as psychologists are
still trying to figure out how humans work.
Thus, we get this mass of much smaller and concentrated fields, attempting to solve just one area
that might be considered a part of intelligence.
The many applications of AI include robotics, planning, vision, speech expert systems, natural language
processing and machine learning.
Notice how machine learning is just one very small part of the whole A.I. Dominion.
A.I., as it is applied in games until recently, could hardly be considered artificial intelligence
in the pure academic sense.
In the academic domain, researchers are trying to produce a truly intelligent machine.
However, game developers are really only interested in simulating intelligence or creating something
that a human player could be tricked into believing was real.
So academic and gaming A.I. are very different beasts, though.
If I had to point to the areas in A.I. where games have pulled inspiration from them most, I would
go to the planning and expert systems.
But if I hear you jumping up and down on your seats, pointing at the screen and screaming, what about
machine learning?
Well, then you're absolutely correct.
In recent years, machine learning has gained a lot of traction in games, as it has the potential to
create game characters with the levels of intelligence to adapt to changes in their environments.
Though to really understand machine learning requires a high level of mathematics and statistics knowledge,
as well as an appreciation of how it can be applied in games.
And currently in about 95% of today's games.
Machine learning would be a complete overkill for the types of functionality that you require.
However, what you're going to learn in this course are the bread and butter techniques of AI in games,
the time honored methods we have been using for decades to get non-player characters, to move around
their environment, interact with the player, and exhibit traits of being digitally alive.
So step in for a fun filled ride through the most tried and true algorithms as we apply them in Unity
with C-sharp.
And I'll show you how you can apply AI to enhance your own game projects in the future.