Soft Computing is a branch of artificial intelligence that focuses on the design of intelligent systems capable of solving complex, imprecise or ambiguous problems. Unlike traditional approaches to artificial intelligence, which are based on logic and computational theory, Soft Computing uses techniques inspired by biology, psychology and other sciences related to human and animal behavior.
The most common techniques used in Soft Computing include artificial neural networks, fuzzy systems, genetic algorithms, swarm optimization and artificial immune systems. These techniques are often used in combination to solve complex problems that are difficult to solve with a single approach.
Soft Computing is used in a wide variety of applications, such as industrial process control, route planning, decision making in uncertain environments, pattern recognition, image classification and natural language processing. Its flexible and adaptable approach makes it a very useful tool in solving real-world problems.
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