Classical propositional logic, metatheorems, semantics and proof theory; nonmonotonic logic; belief change theory; satisfaction in modal and first-order languages; automated reasoning algorithms and SAT-solvers.
The overall aim of this paper is to provide students with sufficient background in applied logic to understand research in logic-based artificial intelligence as published in, for example, the journal Artificial Intelligence. The emphasis is on the acquisition of technical skills and, in particular, on facility with propositional languages of various sorts (although first-order logic is also treated).
| Paper title | Logic for Artificial Intelligence |
|---|---|
| Paper code | COSC410 |
| Subject | Computer Science |
| EFTS | 0.1667 |
| Points | 20 points |
| Teaching period | Not offered in 2022 (On campus) |
| Domestic Tuition Fees (NZD) | $1,371.61 |
| International Tuition Fees | Tuition Fees for international students are elsewhere on this website. |
- Eligibility
- The only background assumed is mathematical maturity (as might be achieved by completing and enjoying at least one MATH paper) and an interest in artificial intelligence or cognitive science. Students who are not skilled programmers will be accommodated in other ways.
- Contact
Computer Science Adviser, adviser@cs.otago.ac.nz
- More information link
- View more information about COSC 410
- Teaching staff
- Lecturers: to be advised
- Paper Structure
The main topics include:
- Classical propositional and first-order logic
- Nonmonotonic logic
- AGM belief revision
- Temporal logic
- Epistemic logic
- Automated reasoning
Assessment:
- Quizzes in lectures 8%
- Two assignments 12% and 10%
- Final exam 70%
- Teaching Arrangements
- One 2-hour lecture per week.
- Textbooks
Textbooks are not required for this paper.
Self-contained lecture notes are supplied via the coursework webpage.- Course outline
- View the course outline for COSC 410
- Graduate Attributes Emphasised
- Communication, Critical thinking.
View more information about Otago's graduate attributes. - Learning Outcomes
- This paper will enable students to appreciate the fundamental roles in logic of concepts, such as satisfaction and model, to understand the limitations of particular approaches to logical formalisation and to develop the skill of formulating clear arguments. Students will be introduced to active research areas in logic that are relevant for artificial intelligence and, more generally, for computer science, such as common-sense reasoning and belief change theory.
