Symbolic AI
Symbolic AI is an approach to artificial intelligence that represents knowledge using explicit symbols, rules, logic, and structured relationships to perform reasoning and solve problems.
What is Symbolic AI?
Symbolic AI uses predefined representations such as facts, rules, logic statements, and knowledge graphs to model information and draw conclusions. Unlike approaches that primarily learn patterns from data, symbolic systems rely on explicit knowledge and reasoning processes that can often be inspected and understood.
Why is Symbolic AI Important?
Symbolic AI can provide transparent and predictable reasoning because the rules and knowledge used by the system are explicitly represented. It is particularly useful when decisions need to follow defined logic, constraints, or domain-specific rules.
Common use cases
Symbolic AI is commonly used in expert systems, knowledge graphs, automated reasoning, rule-based automation, planning, theorem proving, and applications requiring explainable decision-making.