Hide menu

Artificial Intelligence

FDA006, 2007HT

Status Archive
School National Graduate School in Computer Science (CUGS)
Division AIICS
Owner Erik Sandewall
Homepage http://www.ida.liu.se/cugs/CCC-ArtificialIntelligence

  Log in  




Course plan

Lectures

24 hours

Recommended for

Doctoral students in computer science.

The course was last given

2006

Goals

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

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.

Organization

Lectures.

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

Literature

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

Lecturers

Erik Sandewall

Examiner

Erik Sandewall

Examination

Exam and assignment

Credit

4,5 hp (3) credits

Comments

Course webpage

http://piex.publ.kth.se/courses/cugs-ai/


Page responsible: Webmaster
Last updated: 2012-05-03