Computational Intelligence and the thin line of demarcation it forms with artificial intelligence
Introduction
Computational intelligence is the process by which a machine learns to execute tasks with the help of observation data. In simple terms, we can regard the process of computational intelligence as similar to soft computing but different from artificial intelligence. In this way, it lies somewhere between soft computing and artificial intelligence and there is no accepted definition or terminology for this newly emerging field of intelligence.
The gradual progress and transformation of artificial intelligence has given rise to various sub domains within this prospective field. Computational intelligence is one such sub field. It is slowly making its way into artificial intelligence courses in India because it is inspired from the same methodologies that laid the foundation of artificial intelligence. In addition to this, it is also the perfect field to tackle the real world challenges and derive solutions to them with the help of computational and statistical methods.
The birth of computational intelligence
Computational intelligence did not have a sudden birth. It evolved out of the different methodologies that were employed for carrying out research and development in the field of artificial intelligence. Computational intelligence owes its origin to five important methodologies and computational techniques.
- The first important technique is called Fuzzy logic. Fuzzy logic provides the medium through which a machine is able to comprehend the meaning of human language.
- The second important part of computational intelligence includes artificial neural networks that are conceived with the aim of enabling the machine to act like the human brain. This also means that artificial neural networks work with the help of different functions by breaking down a task into different subsets, deriving solutions and communicating them as an output.
- The third important part of computational intelligence is evolutionary computing. As the name indicates, evolutionary computing is derived from the theory of natural selection by clubbing it with the principles of probability. This is an extremely important part of computational intelligence as it allows it to handle different uncertainty problems with a lot of ease.
- The fourth important part of computational intelligence is inspired by advanced algorithms like swarm intelligence. Swarm intelligence has been itself inspired from various biological approaches and methodologies while simultaneously keeping the statistical principles intact.
- The fifth important part of computational intelligence includes artificial immune systems. Artificial immune systems make use of different techniques like natural language processing, machine learning and artificial intelligence. The birth of the artificial immune system was inspired by the working of the human immune system including the various signals that are transmitted between nerves. So, artificial immune systems provide the power of very strong algorithms and stand at the epicenter of computational intelligence.
Thin line of demarcation between artificial Intelligence and computational Intelligence
Why we say that there is a thin line of demarcation between artificial Intelligence and computational intelligence is because the goals of both these technologies are one and the same. While the short term goal of these technologies is to derive solutions to various problems and challenges faced by human beings, the long term goal is to achieve the state of General Intelligence. In the state of General Intelligence, machines are able to perform various tasks of humans in a synchronized manner with a similar or higher degree of efficacy.
While computational intelligence can be regarded as a subset of artificial intelligence, the recent advancements in computational intelligence have made it depart from its parent field. Computational intelligence has evolved at a brisk pace as compared to artificial intelligence due to a reliance on different soft computing methods that allow this technology to be employed in different situations.
Application domains
However, when it comes to the application domain, we conclude that artificial intelligence has a higher influence on various fields as compared to computational intelligence. Artificial intelligence is being used in different sectors like finance, education, healthcare, communication, retail, logistics, e-commerce, supply chain networks, logistics, tourism, energy, shipping, transportation and the like.
Research and development
The research and development that is being carried out in artificial intelligence is second to none. On the other hand, the applications of computational intelligence are prospective but still at the juvenile stage. One of the prospective application fields of computational intelligence is bio-medicine. Since computational intelligence leverages the power of evolutionary computation as well as artificial immune systems, its application to the field of biological systems is simply phenomenal.
Principles of computational intelligence
The main principles of computational intelligence can be understood from various broad perspectives.
- The first principle of computational intelligence relies on quantitative and statistical methods to carry out different processes. This field of study lays impetus on process modeling to understand and make sense of different tasks.
- The second principle of computational intelligence relies on the understanding of real life biological processes. By making sense of these biological processes with the help of evolutionary computation, it becomes easy to derive more substantial and organic solutions to real life problems.
- The third important principle of computational intelligence is its dependance on learning theory. With the help of this principle, computational intelligence comes very close to the sphere of reasoning of human beings. In simple terms, computational intelligence makes use of psychological domain and theories to enrich its subject matter. The understanding of cognitive principles allows computational intelligence to understand real life problems from an emotional and humane lens. This has not been done by artificial intelligence ever before due to its close proximity with machine learning and deep learning techniques.
- In addition to this, computational intelligence also endeavors to harness the power of knowledge and skills that are made use of by humans to solve real life problems.
- We conclude that the domain of computational intelligence not only lays focus on quantitative and statistical methods but also on cognitive and emotional elements to derive meaningful solutions.
Conclusion
With the help of probability methods, the functionality and applications of computational intelligence would increase in the time to come. The need of the hour is to integrate the field with artificial intelligence in its truest sense so that this integration leads to a technology driven future where machines derive empathetic solutions to real life problems.
