AI Definitions: Symbolic Artificial Intelligence

Symbolic Artificial Intelligence – The dominant area of research for most of AI’s history until artificial neural networks became the center of most of the recent developments in artificial intelligence. Symbolic AI requires programmers to meticulously define the rules that specify the behavior they want from an intelligent system. It works well when the environment is predictable, and the rules are clear-cut. Researchers believed if they  programmed enough rules and logic into computers, they could create machines capable of human-like reasoning.  Despite the fact that symbolic AI has lost its luster in the last few years, most of the applications we use today are rule-based systems. An alternative approach to AI is machine learning. Some believe the future of AI lies in a hybrid combination of these approaches.

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