Which subfield uses symbols and explicit rules to represent knowledge for reasoning?

• A. Symbolic AI
• B. Probabilistic Reasoning
• C. Reinforcement Learning
• D. Unsupervised Learning

Answer: (A)

Symbolic AI uses symbols and explicit rules to represent knowledge for reasoning. Facts are encoded as symbols and reasoning proceeds by applying logical or production rules to derive new conclusions or guide actions. This makes the reasoning process transparent because you can trace exactly which rules produced a given result. For example, a rule might say that if a person is over 18 and has a driver's license, they may rent a car. Unlike probabilistic reasoning, which handles uncertainty with probabilities, symbolic AI relies on discrete symbols and deterministic rules; it differs from reinforcement learning and unsupervised learning, which focus on learning patterns or policies from data rather than manipulating explicit symbolic knowledge for deduction.