Introduction To Artificial Intelligence

Artificial intelligence (AI) is the field that studies the synthesis and analysis of computational agents that act intelligently. Let us examine each part of this definition. An agent is something that acts in an environment – it does something. Agents include worms, dogs, thermostats, airplanes, robots, humans, companies, and countries. We are interested in what an agent does; that is, how it acts. We judge an agent by its actions.

An agent acts intelligently when

What it does is appropriate for its circumstances and its goals,
It is flexible to changing environments and changing goals,
It learns from experience, and
It makes appropriate choices given its perceptual and computational limitations.

An agent typically cannot observe the state of the world directly; it has only a finite memory and it does not have unlimited time to act. A computational agent is an agent whose decisions about its actions can be explained in terms of computation. That is, the decision can be broken down into primitive operation that can be implemented in a physical device. This computation can take many forms. In humans this computation is carried out in “wetware”; in computers it is carried out in “hardware.” Although there are some agents that are arguably not computational, such as the wind and rain eroding a landscape, it is an open question whether all intelligent agents are computational. The central scientific goal of AI is to understand the principles that make intelligent behavior possible in natural or artificial systems.

This is done by

The analysis of natural and artificial agents;
Formulating and testing hypotheses about what it takes to construct intelligent agents; and
Designing, building, and experimenting with computational systems that perform tasks commonly viewed as requiring intelligence.

As part of science, researchers build empirical systems to test hypotheses or to explore the space of possibilities. These are quite distinct from applications that are built to be useful for an application domain. Note that the definition is not for intelligent thought.We are only interested in thinking intelligently insofar as it leads to better performance. The role of thought is to affect action. The central engineering goal of AI is the design and synthesis of useful, intelligent artifacts.We actually want to build agents that act intelligently. Such agents are useful in many applications.

Artificial and Natural Intelligence:

Artificial intelligence (AI) is the established name for the field, but the term “artificial intelligence” is a source of much confusion because artificial intelligence may be interpreted as the opposite of real intelligence.

Figure 1.1: A possible dialog for the Turing test

Interrogator: In the first line of your sonnet which reads “Shall I compare thee to a summer’s day,” would not ”a spring day” do as well or better?
Witness: It wouldn’t scan.
Interrogator: How about “a winter’s day,” That would scan all right.
Witness: Yes, but nobody wants to be compared to a winter’s day.
Interrogator: Would you say Mr. Pickwick reminded you of Christmas?
Witness: In a way.
Interrogator: Yet Christmas is a winter’s day, and I do not think Mr. Pickwick would mind the comparison.
Witness: I don’t think you’re serious. By a winter’s day one means a typical winter’s day, rather than a special one like Christmas.

For any phenomenon, you can distinguish real versus fake, where the fake is non-real. You can also distinguish natural versus artificial. Natural means occurring in nature and artificial means made by people.

Example 1.1 A tsunami is a large wave in an ocean caused by an earthquake or a landslide. Natural tsunamis occur from time to time. You could imagine an artificial tsunami that was made by people, for example, by exploding a bomb in the ocean, yet which is still a real tsunami. One could also imagine fake tsunamis: either artificial, using computer graphics, or natural, for example, a mirage that looks like a tsunami but is not one.

Solution: It is arguable that intelligence is different: you cannot have fake intelligence. If an agent behaves intelligently, it is intelligent. It is only the external behavior that defines intelligence; acting intelligently is being intelligent. Thus, artificial intelligence, if and when it is achieved, will be real intelligence created artificially.
This idea of intelligence being defined by external behavior was the motivation for a test for intelligence designed by Turing [1950], which has become known as the Turing test. The Turing test consists of an imitation game where an interrogator can ask a witness, via a text interface, any question. If the interrogator cannot distinguish the witness from a human, the witness must be intelligent. Figure 1.1 shows a possible dialog that Turing suggested. An agent that is not really intelligent could not fake intelligence for arbitrary topics. There has been much debate about the Turing test. Unfortunately, although it may provide a test for how to recognize intelligence, it does not provide a way to get there; trying each year to fake it does not seem like a useful avenue of research.

The obvious naturally intelligent agent is the human being. Some people might say that worms, insects, or bacteria are intelligent, but more people would say that dogs, whales, or monkeys are intelligent. One class of intelligent agents that may be more intelligent than humans is the class of organizations. Ant colonies are a prototypical example of organizations. Each individual ant may not be very intelligent, but an ant colony can act more intelligently than any individual ant. The colony can discover food and exploit it very effectively as well as adapt to changing circumstances. Similarly, companies can develop, manufacture, and distribute products where the sum of the skills required is much more than any individual could master.

Modern computers, from low-level hardware to high-level software, are more complicated than any human can understand, yet they are manufactured daily by organizations of humans. Human society viewed as an agent is arguably the most intelligent agent known. It is instructive to consider where human intelligence comes from. There are three main sources:

biology: Humans have evolved into adaptable animals that can survive in various habitats.
culture: Culture provides not only language, but also useful tools, useful concepts, and the wisdom that is passed from parents and teachers to children.
life-long learning: Humans learn throughout their life and accumulate knowledge and skills.

These sources interact in complex ways. Biological evolution has provided stages of growth that allow for different learning at different stages of life. We humans and our culture have evolved together so that humans are helpless at birth, presumably because of our culture of looking after infants. Culture interacts strongly with learning. A major part of lifelong learning is what people are taught by parents and teachers. Language, which is part of culture, provides distinctions in the world that should be noticed for learning.