Artificial Intelligence | Neuro AI – Artificial neural network

Defining Artificial Intelligence

The phrase Artificial Intelligence was first coined by John McCarthy four decades ago. One representative definition is pivoted around comparing intelligent machines with human beings. Another definition is concerned with the performance of machines which historically have been judged to lie within the domain of intelligence.

Yet none of these definitions have been universally accepted, probably because the reference of the word intelligence which is an immeasurable quantity. A better definition of artificial intelligence, and probably the most accurate would be: An artificial system capable of planning and executing the right task at the right time rationally. Or far simpler: a machine that can act rationally.

With all this a common questions arises:

Does rational thinking and acting include all characteristics of an intelligent system?

If so, how does it represent behavioral intelligence such as learning, perception and planning?

If we think a little, a system capable of reasoning would be a successful planner. Moreover, a system can act rationally only after acquiring knowledge from the real world. So the property of perception is a perquisite of building up knowledge from the real world.

With all this we may conclude that a machine that lacks of perception cannot learn, therefore cannot acquire knowledge.

To understand the practical meaning or artificial intelligence we must illustrate some common problems. All problems that are dealt with artificial intelligence solutions use the common term state.

A state represents the status of a solution at a given step during the problem solving procedure. The solution of a problem is a collection of states. The problem solving procedure or algorithm applies an operator to a state to get the next state. Then, it applies another operator to the resulting state to derive a new state.

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Artificial Intelligence | Neuro AI - Artificial neural network

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