CCC-AI
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
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Search and optimization: Heuristic, local and adversarial search
techniques.
-
Planning and Scheduling:
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Partial-order planning, hierarchical planning, graph
planning, heuristic planning, domain-dependent planning.
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Planning under uncertainty, planning with time and
resources.
-
Combining planning and scheduling
-
Learning: Inductive learning, decision trees, classification,
PAC learning, reinforcement learning, learning rules.
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Uncertainty reasoning systems
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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.
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Neural networks
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Software issues in robotics): Behavior-based robotics,
deliberative/reactive architectures, sensing and perceiving,
navigation.
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Knowledge-based expert systems and applications:
Diagnosis/classification, monitoring and control
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Evolutionary computing
-
AI architectures
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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.
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