What Is AI?

What Is AI?

   9:40 PM       Rizkooblogsite

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Artificial intelligence is about making computers able to perform the thinking tasks that humans and animals are capable of.

  We can already program computers to have superhuman abilities in solving many problems: arithmetic, sorting, searching, and so on. We can even get computers to play some board games better than any human being (Reversi or Connect 4, for example). Many of these problems were originally considered AI problems, but as they have been solved inmore and more comprehensive ways, they have slipped out of the domain of AI developers.

  But there are many things that computers aren’t good at which we find trivial: recognizing familiar faces, speaking our own language, deciding what to do next, and being creative. These are the domain of AI: trying to work out what kinds of algorithms are needed to display these properties.

In academia, some AI researchers are motivated by philosophy: understanding the nature of thought and the nature of intelligence and building software to model how thinking might work. Some are motivated by psychology: understanding the mechanics of the human brain and mental processes. Others are motivated by engineering: building algorithms to perform humanlike tasks. This threefold distinction is at the heart of academic AI, and the different mind-sets are responsible for different subfields of the subject.

  As games developers, we are primarily interested in only the engineering side: building algorithms that make game characters appear human or animal-like. Developers have always drawn from academic research, where that research helps them get the job done.

  It is worth taking a quick overview of the AI work done in academia to get a sense of what exists in the subject and what might be worth plagiarizing.We don’t have the room (or the interest and patience) to give a complete walk-through of academic AI, but it will be helpful to look at what kinds of techniques end up in games.

  You can, by and large, divide academic AI into three periods: the early days, the symbolic era, and
the modern era. This is a gross oversimplification, of course, and the three overlap to some extent,
but we find it a useful distinction.