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Course INFO282

Knowledge Representation and Reasoning

Course offered :

Number of credits 10
Course offered (semester) Autumn
Subject overlap The course gives 10 ects credit reduction taken together with INFO281.
Schedule Schedule
Reading list Reading list

Language of Instruction

English

Learning Outcomes

Upon completion of the course the student should be able to:

  • demonstrate command of theoretical knowledge about principles for logic-based representation and reasoning.
  • demonstrate a basic understanding of production systems, frames, inheritance systems and approaches to handling uncertain or incomplete knowledge.
  • demonstrate a basic understanding of principles for reasoning with respect to explanation and planning.
  • analyze and design knowledge based systems intended for computer implementation.
  • demonstrate a broad understanding of how knowledge based systems work which provides a solid foundation for further studies and for assessing when knowledge based approaches to problem solving are appropriate.

Contact Information

advice@info.uib.no

Course offered (semester)

Autumn

Exam offered (semester)

Autumn

Language of Instruction

English

Course Unit Level

Bachelor level

Access to the Course Unit

Open

Aim and Content

The students will learn both theoretical and technical knowledge and research methodology which is valuable for carrying out research in artificial intelligence. Through the course, the students will:

  1. Understand general concepts in artificial intelligence
  2. Learn widely applied techniques for problem solving
  3. Learn how to design intelligence applications

The course provides an introduction to the theoretical and technical issues of artificial intelligence. We will focus on some of the basics common to most areas of AI, such as problem solving, heuristic search, knowledge representation, and reasoning under uncertainty. We will also cover important applications of artificial intelligence including expert systems and agent architectures. Some reflections on and hands-on experience in design and development of intelligent systems will also be offered.

Learning Outcomes

Upon completion of the course the student should be able to:

  • demonstrate command of theoretical knowledge about principles for logic-based representation and reasoning.
  • demonstrate a basic understanding of production systems, frames, inheritance systems and approaches to handling uncertain or incomplete knowledge.
  • demonstrate a basic understanding of principles for reasoning with respect to explanation and planning.
  • analyze and design knowledge based systems intended for computer implementation.
  • demonstrate a broad understanding of how knowledge based systems work which provides a solid foundation for further studies and for assessing when knowledge based approaches to problem solving are appropriate.

Recommended previous knowledge

INFO102 or equivalent. Solid background in programming.

Subject Overlap

The course gives 10 ects credit reduction taken together with INFO281.

Teaching Methods

Lectures and data labs, normally 2 + 2 hours per week for 12-15 weeks.

Compulsory Requirements

3 mandatory assignments.

The assignments must be approved in the teaching semester, and they are valid in this and the following semester.

Assessment methods

Written exam 4 hours.

Grading Scale

The grading system has a descending scale from A to E for passes and F for fail.

Course Unit Evaluation

INFO282 is evaluated by students every three years, by the Department every year.

Contact Information

advice@info.uib.no