Ans:- Artificial Intelligence is the study of how to make computers do things, which at the moment, people can do better.
History of AI:- Although the computer provided the technology necessary for AI, it was not until the early 1950's that the link between human intelligence and machines was really observed. Norbert Wiener was one of the first Americans to make observations on the principle of feedback theory feedback theory. The most familiar example of feedback theory is the thermostat: It controls the temperature of an environment by gathering the actual temperature of the house, comparing it to the desired temperature, and responding by turning the heat up or down. What was so important about his research into feedback loops was that Wiener theorized that all intelligent behavior was the result of feedback mechanisms. Mechanisms that could possibly be simulated by machines. This discovery influenced much of early development of AI.
Importance of AI:- The subject of artificial intelligence was originated with game-playing and theoremproving programs and was gradually enriched with theories from a number of parent disciplines.
Learning Systems: Among the subject areas covered under artificial intelligence, learning systems needs special mention. The concept of learning is illustrated here with reference to a natural problem of learning of pronunciation by a child from his mother.
Knowledge Representation and Reasoning: In a reasoning problem, one has to reach a predefined goal state from one or more given initial states. So, the lesser the number of transitions for reaching the goal state, the higher the efficiency of the reasoning system.
Planning: Another significant area of artificial intelligence is planning. The problems of reasoning and planning share many common issues, but have a basic difference that originates from their definitions.
Knowledge Acquisition: Acquisition (Elicitation) of knowledge is equally hard for machines as it is for human beings. It includes generation of new pieces of knowledge from given knowledge base, setting dynamic data structures for existing knowledge, learning knowledge from the environment and refinement of knowledge.
Logic Programming: For more than a century, mathematicians and logicians were used to designing various tools to represent logical statements by symbolic operators. One outgrowth of such attempts is propositional logic, which deals with a set of binary statements (propositions) connected by Boolean operators.
Soft Computing: Soft computing, according to Prof. Zadeh, is "an emerging approach to computing, which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision”.