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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course EDAF70F valid from Spring 2017

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General
Aim
  • To give an introduction to several subdomains of artificial intelligence and to give an orientation about fundamental methods within these domains. To convey knowledge about breath and depth of the domain.
Contents
  • Intelligent agents. Heuristic search. Game programming. Knowledge based systems. Machine learning. Natural language. Semantic Web. Autonomous robots. Planning.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • display basic knowledge concerning theories and methods related to the following subdomains: intelligent agents, heuristic search, game programming, knowledge representation, knowledge-based systems, probabilistic reasoning, machine learning, natural language processing.
Competences and Skills
  • For a passing grade the doctoral student must
  • complete a number of assignments based on problems related to some of the following subdomains: heuristic search, knowledge-based systems, probabilistic reasoning, machine learning, natural language processing.
Judgement and Approach
  • For a passing grade the doctoral student must
  • demonstrate the ability to critically evaluate and compare different methods used in artificial intelligence.
Types of Instruction
  • Lectures
  • Laboratory exercises
Examination Formats
  • Written exam
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • EDAA01 Programming - Second Course
Selection Criteria
Literature
  • Stuart Russell, P.: Artificial Intelligence , A Modern Approach. Pearson, 2010. ISBN 0132071487.
Further Information
Course code
  • EDAF70F
Administrative Information
  •  -03-22
  • Professor Thomas Johansson

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