Artificial Intelligence: Symbolic Methods in AI

Symbolic methods in AI assume that knowledge can be represented by means of symbols that can further be manipulated in order to perform reasoning and problem-solving tasks. These methods rely on formal logic and symbolic representations, such as knowledge graphs or rule-based systems, to model relationships and infer new information. Since symbolic AI can be successfully exploited in applications requiring explicit rules and structured knowledge, such as expert systems and natural language processing, during the course we will discuss the most important tools used in this paradigm of AI, such as propositional and first-order logic, description logics, knowledge graphs, or the Datalog language.