Course Title

Artificial Intelligence

Course Type

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

Periodicity

Once a year

Suggested # of Credits

4.5 HE Credits (Higher Education Credits)

Intended audience

Doctoral students in computer science.

Goal

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.

Prerequisites

Introductory course in artificial intelligence.

Related courses

Knowledge Representation

Contents

• 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

Organization

See course schedule.

Examination

Exam and assignment

Literature

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

Examiner

Erik Sandewall

Course homepage

Not available.

Other information

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