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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

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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: Director of Graduate Studies