Symbolic AI systems are AI approaches that represent knowledge in the form of discrete symbols and explicit rules and process it through logical inference.
They use formal logics, such as predicate logic, to represent knowledge, and inference-based methods to derive new insights.
Such systems are also called knowledge-based systems or expert systems and enable explainable and deterministic decisions.
A typical example is a rule-based system, which consists of if-then rules and applies them to problem-solving.
Definition:
“Symbolic AI systems represent knowledge explicitly with symbols and rules, applying logical inference to manipulate these symbols for reasoning and decision-making.”
Source:
Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson.