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Artificial Intelligence, 6 credits
Artificiell intelligens, 6 hp
TDDC17
Main field of study
Computer Science and Engineering Computer ScienceCourse level
First cycleCourse type
Programme courseExaminer
Patrick DohertyDirector of studies or equivalent
Peter DaleniusEducation components
Preliminary scheduled hours: 52 hRecommended self-study hours: 108 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
Main field of study
Computer Science and Engineering, Computer ScienceCourse level
First cycleAdvancement level
G2XCourse offered for
- Computer Science, Master's Programme
- Computer Science and Software Engineering, M Sc in Engineering
- Computer Engineering, B Sc in Engineering
- Programming
- Mathematics
- Computer Science and Engineering, M Sc in Engineering
- Industrial Engineering and Management - International, M Sc in Engineering
- Industrial Engineering and Management, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Programming in a functional, imperative or object oriented programming language. Knowledge of data structures and algorithms. Knowledge in logic and discrete mathematics is useful.Intended learning outcomes
The aim of the course is to introduce concepts and applications of artificial intelligence (AI). Focus is on developing intelligent agent systems that can decide what to do and do it. This requires techniques for problem solving, knowledge and reasoning, learning, communication, perceiving and acting. After the course the student will be able to:
- explain and discuss artificial intelligence concepts
- apply well known artificial intelligence techniques
Course content
Overview of AI and its applications. Search as a problem-solving method. Logic as a means of representing knowledge. Reasoning with incomplete information; nonmonotonic and probabilistic reasoning. Structured knowledge representation. Action planning and robotics. Strategies for automatic learning. Orientation in architectures for AI.
Teaching and working methods
The course consists of a series of lectures devoted to theory and
laboratory work where different AI techniques are practised using Common Lisp or Java.
Examination
| LAB1 | Laboratory work | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Other information
AI Programming
Department
Institutionen för datavetenskapDirector of Studies or equivalent
Peter DaleniusExaminer
Patrick DohertyCourse website and other links
Education components
Preliminary scheduled hours: 52 hRecommended self-study hours: 108 h
Course literature
Russell, S. & Norvig, P. (2002) Artificial Intelligence: A Modern Approach, Prentice Hall. ISBN 0137903952 (inb) 0130803022 (hft).Laborationskompendium från Institutionen för datavetenskap.
Referenslitteratur: Shapiro, C. (1992) Encyclopedia of Artificial Intelligence, Vol. 1-2, Wiley Interscience.
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| LAB1 | Laboratory work | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
Russell, S. & Norvig, P. (2002) Artificial Intelligence: A Modern Approach, Prentice Hall. ISBN 0137903952 (inb) 0130803022 (hft).
<br>Laborationskompendium från Institutionen för datavetenskap.
<br>Referenslitteratur:
Shapiro, C. (1992) Encyclopedia of Artificial Intelligence, Vol. 1-2, Wiley Interscience.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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X
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LAB1
TEN1
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| 1.2 Fundamental engineering knowledge (G1X level) |
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X
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X
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LAB1
TEN1
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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X
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LAB1
TEN1
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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X
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X
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LAB1
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| 2.2 Experimentation, investigation, and knowledge discovery |
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X
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X
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LAB1
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| 2.3 System thinking |
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| 2.4 Attitudes, thought, and learning |
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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X
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LAB1
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| 3.2 Communications |
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
X
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| 4.4 Designing |
X
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| 4.5 Implementing |
X
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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