Adaptive neural networks classify patterns. Input data similar to previously seen patterns are classified as one of them. Patterns not similar to previous ones have a new class of patterns created for them.
In artificial neural networks, training time of some networks can be decreased by the use of an adaptive learning rate which attempts to keep the learning step size as large as possible while keeping learning stable. The learning rate is made responsive to the complexity of the local error surface.
A term used to describe problems or subproblems in artificial intelligence, to indicate that the solution presupposes a solution to the "strong AI problem" (that is, the synthesis of a human-level intelligence). A problem that is AI-complete is, in other words, just too hard.
The predominant character set encoding of present-day computers. The modern version uses seven bits for each character, whereas most earlier codes (including an early version of ASCII) used fewer.
(AI) The subfield of computer science concerned with the concepts and methods of symbolic inference by computer and symbolic knowledge representation for use in making inferences. AI can be seen as an attempt to model aspects of human thought on computers. It is also sometimes defined as trying to solve by computer any problem that a human can solve faster.
(a-life) The study of synthetic systems which behave like natural living systems in some way. Artificial Life complements the traditional biological sciences concerned with the analysis of living organisms by attempting to create lifelike behaviours within computers and other artificial media.
Automatic, as opposed to human, operation or control of a process, equipment or a system; or the techniques and equipment used to achieve this. Most often applied to computer (or at least electronic) control of a manufacturing process.
