Throughout history humans have attempted to gain a better understanding of the wokrings of the mind. How can we percieve, understand, predict and even manipulate a world far greater and more complex than we are? The term "artificial intelligence" was coined in 1956. Since then, scientists in the field have attempted not only to understand but to also create intelligent entities. AI encompasses many different subfields ranging from machine learning and perception to game theory and complex mathematical analysis. The goal of artificial intelligence is to create a machine that can not only think and act like a human being--or perhaps, even more rationally.
For thousands of years scientists in different fields have posed questions that would eventually lead to the birth of artificial intelligence. Philosophers from around the 5th century to the present have asked themselves: Can formal rules be used to draw valid conclusions? How does the mental mind arise from the physical brain? Where does knowledge come from and how does it lead to action? Since ancient times mathematicians, including George Boole, Euclid and others have posed such questions as: What are the formal rules to draw valid conclusions? What can be computed and how should one reason with uncertain information? Economics, born as a science in late 1770s, is another field that has attempted to reason human behaivior in order to approximate the profit of a given transaction. The development of the decision theory which combines both the theory of porbability andutility theory provided one of the earliest formal and complete frameworks for decisions made under uncertainty. The field of neurosciece, from roughly 1860 to the present, has attemtped to uncover how rains process information, giving us an insight into the meachanical workings of the brain. Psychology has further analysed the behaivior of human beings in comparison to other animals. Linguistics, the study of verbal behaivior, has led to the question of how language relates to thought. Finally the development of computer engineering in the 1940s and the deisre to build efficient and rational tools gave birth to the field of artificial intelligence.
The first work in the field was done by Warren McCulloch and Walter Pitts. Drawing on the knowledge of basic physiology and the functionality of the brain, the formal analysis of propositional logic and Turing's theory of computation, they proposed a model of an artificial neuron. In 1956, John McCarthy, another very influencial figure in the field brought together researchers intereted in automata theory, meural nets, and study of intelligence organizing a workshop on what later became known as artificial intelligence. The early days of AI were full of success and great expectations, however by mid-1960s some difficulties arose. Most early programs contained little or no knowlegde of the subject matter, the many problems that AI was trying to solve became intractible and finally there were some fundamental limitations on the basic structures bein used to generate iuntelligent behaivior. Creating a knowlegde based system seemed to be the optimal answer. Domain-specific knowledge would allow larger reasoning steps handling typical narrow problems. In early 1980s AI became an industry of its own, but by the end of the decade, with the return of the neural network approach, AI turned into a scientific rather than a comercial field. Artificial intelligence has advanced very rapidly in the last 10 years because of the greater use of the scientific method in experimenting and comparing approaches. The growth of AI has gone hand in hand with improvements and capabilities of real systems leading to a greater integration of AI and other disciplines.