Computational Intelligence
What is Computational Intelligence?
Computational Intelligence refers to a set of nature-inspired computational methodologies and techniques that enable systems to adopt an intelligent behavior. It encompasses various areas including but not limited to:- Neural Networks: Inspired by biological neural networks, these algorithms are used for pattern recognition, classification, and regression tasks. They learn from data by adjusting connections (weights) based on the input-output relationships.
- Fuzzy Logic: This approach deals with reasoning that is approximate rather than fixed and exact. It is useful for dealing with uncertainty and imprecision in data, and is widely applied in control systems and decision-making processes.
- Evolutionary Computation: Techniques like genetic algorithms, genetic programming, and evolutionary strategies are used to solve optimization and search problems by mimicking the process of natural evolution, allowing solutions to evolve over generations.
- Swarm Intelligence: Inspired by social behaviors of animals such as birds and fish, this approach involves algorithms that focus on solving problems through the collective behavior of decentralized, self-organized systems.
- Artificial Immune Systems: This field draws inspiration from the biological immune system to develop algorithms for anomaly detection, problem solving, and optimization.
Computational Intelligence is particularly effective in dealing with complex problems where traditional approaches may struggle, making it widely applicable in fields such as robotics, computer vision, data mining, and artificial intelligence. As these methods often work by learning from data, they are well-suited for handling real-world scenarios where information may be uncertain or incomplete.
- Snippet from Wikipedia: Computational intelligence
The expression computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.
Generally, computational intelligence is a set of nature-inspired computational methodologies and approaches to address complex real-world problems to which mathematical or traditional modelling can be useless for a few reasons: the processes might be too complex for mathematical reasoning, it might contain some uncertainties during the process, or the process might simply be stochastic in nature. Indeed, many real-life problems cannot be translated into binary language (unique values of 0 and 1) for computers to process it. Computational Intelligence therefore provides solutions for such problems.
The methods used are close to the human's way of reasoning, i.e. it uses inexact and incomplete knowledge, and it is able to produce control actions in an adaptive way. CI therefore uses a combination of five main complementary techniques. The fuzzy logic which enables the computer to understand natural language, artificial neural networks which permits the system to learn experiential data by operating like the biological one, evolutionary computing, which is based on the process of natural selection, learning theory, and probabilistic methods which helps dealing with uncertainty imprecision.
Except those main principles, currently popular approaches include biologically inspired algorithms such as swarm intelligence and artificial immune systems, which can be seen as a part of evolutionary computation, image processing, data mining, natural language processing, and artificial intelligence, which tends to be confused with Computational Intelligence. But although both Computational Intelligence (CI) and Artificial Intelligence (AI) seek similar goals, there's a clear distinction between them.
Computational Intelligence is thus a way of performing like human beings. Indeed, the characteristic of "intelligence" is usually attributed to humans. More recently, many products and items also claim to be "intelligent", an attribute which is directly linked to the reasoning and decision making.
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External links:
- Computational intelligence - Wikipedia — en.wikipedia.org
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- Computational Intelligence (CI) refers to the ability of a computer to learn a specific task from data or experimental observation. It is a set of nature-inspired computational methodologies and approaches that are used when traditional mathematical reasoning might be too complex or contain uncertainties. CI is often considered a subset of Artificial Intelligence (AI), with a clear distinction between the two. While both aim to perform tasks similar to human beings, CI specifically focuses on learning and adaptation, often inspired by biological and linguistic paradigms.
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- From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community with a vision for addressing real-world issues with biologically-motivated computational paradigms. The Society offers leading research in nature-inspired problem solving, including neural networks, evolutionary algorithms, fuzzy systems, and hybrid intelligent systems. Members contribute to the theory, design, application, and development of biologically and linguistically motivated computational paradigms, emphasizing neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained.
- Computational Intelligence — larksuite.com
- Discover a Comprehensive Guide to computational intelligence: Your go-to resource for understanding the intricate language of artificial intelligence.