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A brief history of artificial intelligence

When computers were first built, their speed of numerical computations convinced most people that the following fallacy was true:

• Computers have more computational power than the human brain

Now, computers are millions of times faster than they were fifty years ago. Still, I would argue that for many tasks, this statement is still a fallacy.

Human brains seem to be far "faster" than computers for a wide variety of tasks; for example:

• Recognizing human faces in photographs
• Driving a car using computer vision
• Some types of associative memory recall

Still, greater computational speed does make some so-called AI systems seem smarter. Very good examples of this are computer games that use search techniques. I have been interested in writing computer chess and Go programs for a long time (I wrote the BASIC chess program on the demo cassette tape for the Apple II computer, and I wrote and marketed a commercial Go program, Honninbo Warrior, also for the Apple II).

This short "book" covers the very rudiments of AI search techniques: we initially cover depth first and then breadth first search of networks. We will discuss how to add heuristics to the breadth first search.

A network is defined as a set of nodes and a set of bi-directional links connecting these nodes.

Unless you are not at all curious, you have already tried running the two example Java applets that appeared to the right of the table of contents of this book. Each applet has a network of nine nodes, with several links (e.g., connecting node 0 to node 1, 2 to 3, 2 to 4, etc.). Each Java applet tries to find a path from the starting node to the goal node. In the two sample applets, you can change the starting node and the goal node by using the Java AWT (abstract window toolkit) choice controls.

The development of search techniques was considered to be one of the early successes of AI research.

There are many techniques of AI programming that are not covered here (e.g., expert systems, neural networks, planning, etc.). Also, the material on search in this "book" is very rudimentary, and is written for home hobbiest-programmers.

Next : Why search algorithms are not AI

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