Machine Learning, AI and Soft Computing

Question

What is the difference between these three strongly related fields? Is there any specific whole, all of them are part (except CS)?

Answer 1

Machine science can be considered part of AI, but I would classify Machine Science as a study of the creation of semantic models and adaptive behavior with AI, being a general science of systems that seem reasonable.

Most of what goes as “AI” is quite simplified, but very effective, such as heuristics, etc.

Soft Computing does not crash because it has many ML and AI components, since it is more about analyzing complex systems. I could be wrong. As in most cases in computer science, the deeper you dig, the more you find that it is all connected.

Answer 2

AI is an intelligent project that attempts to capture all aspects of human intelligence in computers. Another project, also called AI, aims to use humanoid algorithms to approximate traditionally insoluble problems. AI can be said to cover areas such as robotics, planning, reasoning, learning and understanding natural language.

Machine science is a discipline that tries to improve machine performance in the task given in the examples. It can be considered as a field of interest for AI, but researchers in the field of machine learning do not have intellectual shares in the overall success of AI. Machine learning is closely aligned with statistical physics and some topics in signal processing, and some formulations strongly overlap planning, control theory, and dynamic programming.

Soft computing includes processes that include indirect, approximate solutions instead of binary algorithms, which are widely regarded as including technologies such as fuzzy logic, neural networks, and genetic algorithms. There is a broad agreement between these methods and a specific subset of AI planning and training, control theory, theory of complex systems, etc.