| Students gain hands-on experience in logic programming, learning to apply Prolog and logic-based database query languages like Datalog to solve practical problems. They acquire the skills to implement inductive logic programming and relational learning algorithms, such as Foil, Progol, and Aleph, on real-world datasets.
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- Programming in Prolog (k5)
Students can write and execute logic programs using Prolog, applying formal logic principles to solve complex queries and reasoning tasks.
- Querying Databases with Datalog (k5)
Students are able to use Datalog for querying and manipulating logic-based databases, understanding its applications in AI for knowledge representation and data retrieval.
- Implementing Inductive Logic Programming (k5)
Students can apply inductive logic programming techniques, using algorithms like Foil and Progol to automatically learn rules from data and generate knowledge representations.
- Using Relational Learning Algorithms (k5)
Students are capable of implementing relational learning algorithms, such as Aleph, to discover patterns and relationships in structured data, building models based on logic-based learning techniques.
- Applying Logic-Based Learning to Practical Problems (k5)
Students can employ logic-based learning algorithms on practical datasets, solving real-world problems by automating the learning and discovery of rules in knowledge-based systems.
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Students acquire practical knowledge in logic programming using Prolog and Datalog, gaining experience in querying logic-based databases. They also learn to implement inductive logic programming and relational learning algorithms like Foil, Progol, and Aleph, applying these techniques to automate knowledge discovery and solve practical AI problems.
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