Opportunities and Challenges for Next-Generation Applied Intelligence
The term “Artificial Intelligence” has been used since 1956 and has become a very popular research field. Generally, it is the study of the computations that enable a system to perceive, reason and act. In the early days, it was expected to achieve the same intelligent behavior as a human, but found impossible at last. Its goal was thus revised to design and use of intelligent methods to make systems more ef- cient at solving problems. The term “Applied Intelligence” was thus created to represent its practicality. It emphasizes applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation, robotics, business, finance, medicine, bio-medicine, bio-informatics, cyberspace, and man-machine interactions. To endow the intelligent behavior of a system, many useful and interesting techniques have been developed. Some of them are even borrowed from the na- ral observation and biological phenomenon. Neural networks and evolutionary computation are two examples of them. Besides, some other heuristic approaches like data mining, adaptive control, intelligent manufacturing, autonomous agents, bio-informatics, reasoning, computer vision, decision support systems, expert systems, fuzzy logic, robots, intelligent interfaces, internet technology, planning and scheduling, are also commonly used in applied intelligence.
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Opportunities and Challenges for Next-Generation Applied Intelligence
The term “Artificial Intelligence” has been used since 1956 and has become a very popular research field. Generally, it is the study of the computations that enable a system to perceive, reason and act. In the early days, it was expected to achieve the same intelligent behavior as a human, but found impossible at last. Its goal was thus revised to design and use of intelligent methods to make systems more ef- cient at solving problems. The term “Applied Intelligence” was thus created to represent its practicality. It emphasizes applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation, robotics, business, finance, medicine, bio-medicine, bio-informatics, cyberspace, and man-machine interactions. To endow the intelligent behavior of a system, many useful and interesting techniques have been developed. Some of them are even borrowed from the na- ral observation and biological phenomenon. Neural networks and evolutionary computation are two examples of them. Besides, some other heuristic approaches like data mining, adaptive control, intelligent manufacturing, autonomous agents, bio-informatics, reasoning, computer vision, decision support systems, expert systems, fuzzy logic, robots, intelligent interfaces, internet technology, planning and scheduling, are also commonly used in applied intelligence.
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Opportunities and Challenges for Next-Generation Applied Intelligence
344
Opportunities and Challenges for Next-Generation Applied Intelligence
344Hardcover(2009)
$169.99
169.99
In Stock
Product Details
ISBN-13: | 9783540928133 |
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Publisher: | Springer Berlin Heidelberg |
Publication date: | 05/20/2009 |
Series: | Studies in Computational Intelligence , #214 |
Edition description: | 2009 |
Pages: | 344 |
Product dimensions: | 6.10(w) x 9.25(h) x 0.03(d) |
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