## Knowledge Representation - COMP97059

### Aims

Knowledge representation and reasoning are essential components of an intelligent system and are at the core of Artificial Intelligence research. The aim of this module is to provide the students with several computational concepts and tools that have been developed in logic-programming or otherwise symbolic reasoning, to support the knowledge representation and inference.

The material covered in the module will interleave the computational concepts of logic programming with applications of the concepts in knowledge representation and problem solving.

More specifically, the module will:

- Recap basic definitions from first-order logic as a necessary preliminary.
- Define definite logic programs, normal logic programs, core semantics for each and stratification. Define stable models, answer-set semantics and splitting sets.
- Present the syntax of Answer Set Programming (ASP), and their use for:
- Defeasible reasoning
- Solving combinatorial problems
- Solving optimisation problems using preferences

- Define the action language C+ and its use for reasoning about action and change, causal reasoning, and planning.
- Present fundamental work on properties of non-monotonic reasoning formalisms, and give a view of the way in which different formalisms satisfy or fail to satisfy these properties.

### Role

Course Leader

## Knowledge Representation - COMP70030

### Aims

Knowledge representation and reasoning are essential components of an intelligent system and are at the core of Artificial Intelligence research. The aim of this module is to provide the students with several computational concepts and tools that have been developed in logic-programming or otherwise symbolic reasoning, to support the knowledge representation and inference.

The material covered in the module will interleave the computational concepts of logic programming with applications of the concepts in knowledge representation and problem solving.

More specifically, the module will:

- Recap basic definitions from first-order logic as a necessary preliminary.
- Define definite logic programs, normal logic programs, core semantics for each and stratification. Define stable models, answer-set semantics and splitting sets.
- Present the syntax of Answer Set Programming (ASP), and their use for:
- Defeasible reasoning
- Solving combinatorial problems
- Solving optimisation problems using preferences

- Define the action language C+ and its use for reasoning about action and change, causal reasoning, and planning.
- Present fundamental work on properties of non-monotonic reasoning formalisms, and give a view of the way in which different formalisms satisfy or fail to satisfy these properties.

### Role

Course Leader