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Born in the United States around 1965, fuzzy set theory has grown to become a major scientific domain collectively referred to in this article as 'fuzzy systems,' which include fuzzy […]

Born in France in the early 1970s, Prolog (PROgramming in LOGic) !7, 11^ was brought to world attention when chosen as the official language for the well-publicized, Japan's Fifth Generation [...]

In commenting on the recent chess match between Garry Kasparov and Deep Blue, IBM has avoided speaking of AI, focusing almost exclusively on its large parallel processor that examines about […]

The practical application of artificial intelligence (AI) has been the center of controversy for many years. Certainly, if we mean AI to be a realization of real human intelligence in […]

The article presents an overview of knowledge discovery or the computer techniques that, in the broadest sense, automatically find fundamental properties and principles. Dealing with more comprehensive, non-oversimplified, real-world types of data, such as mixed data types, is a key direction for the future. It emphasizes the aspects of knowledge discovery that are shared across the various fields of science. Although computers can't crank out major scientific findings every day, they promise to accelerate the rate of significant scientific discoveries. Selected Techniques covers four especially important techniques for knowledge discovery. The notion of computers automatically finding useful information is an exciting and promising aspect of just about any application intended to be of practical use. Replacing such creative human activities as sorting through it all with a computer represents a grand human endeavor. Based on a simulation of the architecture and functioning of the human brain, neural networks are being applied to many types of problems, including pattern recognition, process control, and real-world prediction of real-world phenomena.

The article focuses on principles and applications of chaotic systems. There lies a behavior between rigid regularity and randomness based on chance. It's called a chaotic system, or chaos for short . Chaos is all around the people. Their notions of physical motion or dynamic systems have encompassed the precise clock-like ticking of periodic systems and the vagaries of dice-throwing chance, but have often been overlooked as a way to account for the more commonly observed chaotic behavior between these two extremes. The typical features of chaos are that it is non-linear. It has deterministic underlying rules every future state of the system must follow. Small changes in its initial state can lead to radically different behavior in its final state. This "butterfly effect" allows the possibility that even the slight perturbation of a butterfly flapping its wings can dramatically affect whether sunny or cloudy skies will predominate days later. Long term prediction is mostly impossible in chaotic systems due to sensitivity to initial conditions.

The term artificial intelligence (AI) was coined in 1956 and since that time has come to suggest many things to many people. Machine learning is a well known classical AI area. Its basic idea, the machine gets smarter by itself, is a fascinating concept that every AI researcher dreams of. For example, give a problem to one's personal computer. It then replies that the problem is too difficult to be solved immediately using the current knowledge base. He/She leaves the machine on over night. It keeps working hard, deducing more conclusions and inducing or discovering new rules, internally as well as through a possible outside interaction,such as retrieving necessary information from external knowledge and databases. When he/she come back the next day, the machine has become more knowledgeable than the day before and can solve the problem. Although the number of practical applications of machine learning has been relatively small in comparison with other areas, it is one of the fastest growing areas of AI. Once it is successful, its technical and social aspect will be extremely significant.

Examines the procedures for manipulating multiple stacks which share sequential memory locations. Details on the dynamic initial allocation procedure; Description of the local reallocation procedure; Efficacy of both procedures in improving the operational performance.

Several letters to the editor are presented in response to articles in previous issues including topics on alternative instructional strategy, semantics, style and spelling correction programs and the role of communications.

The result of the much-publicized tournament between IBM's Deep Blue and Garry Kasparov, the World Chess Champion, was Deep Blue with 1 win, 3 loses, and 2 draws. With a […]