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What is symbolic artificial intelligence?

Symbolic artificial intelligence, also known as symbolic AI or classical AI, refers to a type of AI that represents knowledge as symbols and uses rules to manipulate these symbols. Symbolic AI systems are based on high-level, human-readable representations of problems and logic.

How does symbolic AI work?

Symbolic AI works by using symbols to represent objects and concepts, and rules to represent relationships between them. These rules can be used to make inferences, solve problems, and understand complex concepts.

Symbolic AI was the dominant approach in AI research from the 1950s to the 1980s, and it underlies many traditional AI systems, such as expert systems and logic-based AI.

What are the applications and limitations of symbolic AI?

Symbolic AI has been used in a wide range of applications, including expert systems, natural language processing, and game playing. However, it also has limitations. It can be difficult to represent complex, ambiguous, or uncertain knowledge with symbolic AI. Furthermore, symbolic AI systems are typically hand-coded and do not learn from data, which can make them brittle and inflexible.

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