Course Title

Artificial Intelligence

Course Type

CUGS CS Review / CUGS CS Core / CUGS CS Advanced / Other


Once a year

Suggested # of Credits

4.5 HE Credits (Higher Education Credits)

Intended audience

Doctoral students in computer science.


The course is organized under the assumption that your goal, as a participant, will be to acquire a broad and systematic knowledge and understanding of modern artificial intelligence. "Systematic" means that existing cross-connections within the topic should be understood.


Introductory course in artificial intelligence.

Related courses

Knowledge Representation


  • Search and optimization: Heuristic, local and adversarial search techniques.

  • Planning and Scheduling:

    • Partial-order planning, hierarchical planning, graph planning, heuristic planning, domain-dependent planning.

    • Planning under uncertainty, planning with time and resources.

    • Combining planning and scheduling

  • Learning: Inductive learning, decision trees, classification, PAC learning, reinforcement learning, learning rules.

  • Uncertainty reasoning systems

    • Belief networks, decision making under uncertainty, acting under uncertainty

    • Uncertain reasoning: fuzzy logic, probabilistic logic.

  • Decision Making: Utility Theory, beliefs and desires, applications in robotics and on the Internet.

  • Neural networks

  • Software issues in robotics): Behavior-based robotics, deliberative/reactive architectures, sensing and perceiving, navigation.

  • Knowledge-based expert systems and applications: Diagnosis/classification, monitoring and control

  • Evolutionary computing

  • AI architectures

    • Production systems, blackboard architectures, SOAR, belief revision and truth maintenance systems, logic-based systems, multi-agent architectures.

    • Model-based diagnosis and execution monitoring.

Organized by

Department of Computer Science, Linköping University


See course schedule.


Exam and assignment


Stuart Russel and Peter Norvig. "Artificial Intelligence - A Modern Approach", Prentice Hall Series in Artifical Intelligence.

Russell & Norvig textbook webpage can be found here.

Detailed reading list:

Chapters 12-17, 19-21, 24-25 + Lectures notes


Erik Sandewall

Course homepage

Not available.

Other information

The course is given in an intensive format ("crash course") at a conference facility.



Travel reports

Licentiate seminars


Courses Spring 2016


Last modified on March 2008 by Anne Moe