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Multi Agent Systems, 6 credits
Multiagentsystem, 6 hp
TDDE13
Main field of study
Computer Science and Engineering Computer ScienceCourse level
Second cycleCourse type
Programme courseExaminer
Fredrik HeintzDirector of studies or equivalent
Peter DaleniusEducation components
Preliminary scheduled hours: 60 hRecommended self-study hours: 100 h
Available for exchange students
YesECV = Elective / Compulsory / Voluntary
| Course offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
|---|---|---|---|---|---|---|---|
| 6CDDD | Computer Science and Engineering, M Sc in Engineering | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6CDDD | Computer Science and Engineering, M Sc in Engineering (AI and Machine Learning) | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6CMJU | Computer Science and Software Engineering, M Sc in Engineering | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6CMJU | Computer Science and Software Engineering, M Sc in Engineering (AI and Machine Learning) | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6MDAV | Computer Science, Master's programme | 3 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6MICS | Computer Science, Master's programme | 3 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6CITE | Information Technology, M Sc in Engineering | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
| 6CITE | Information Technology, M Sc in Engineering (AI and Machine Learning) | 9 (Autumn 2017) | 2 | 1 | English | Linköping, Valla | E |
Main field of study
Computer Science and Engineering, Computer ScienceCourse level
Second cycleAdvancement level
A1XCourse offered for
- Computer Science and Software Engineering, M Sc in Engineering
- Computer Science and Engineering, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Computer Science, Master's programme
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
An introductory AI course, knowledge of programming, probabilities, and logic.
Intended learning outcomes
The overall aim of the course is to give an overview of multiagent systems and in depth knowledge of some areas of multiagent systems. After the course students should be able to:
- List and explain important problems and techniques in the area of multiagent systems.
- Explain how central algorithms in the area of multiagent systems work. - Be able to implement some central algorithm in the area of multiagent systems.
- Evaluate and apply different game theoretic approaches.
- Design and use auctions for allocating resources in a multiagent system.
- Model relevant aspects of multiagent system decision making using markov decision processes and logics.
Course content
- Architectures for multiagent systems
- Distributed AI, including distributed constraint satisfaction and optimization
- Game theory, including normal form and extensive form games
- Communication, including speech acts
- Aggregated preferences, including voting
- Auctions for multiagent resource allocation
- Logics for multiagent systems
- Multiagent decision-making, including task allocation
Teaching and working methods
Lectures, seminars and labs. Lab assignments will be used to learn more about the practical aspects of multiagent systems and explore some techniques in more detail. The examination will mainly be homework exercises.
Examination
| UPG1 | Assignments | 4 credits | U, 3, 4, 5 |
| LAB1 | Laboratory work | 2 credits | U, G |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Institutionen för datavetenskapDirector of Studies or equivalent
Peter DaleniusExaminer
Fredrik HeintzEducation components
Preliminary scheduled hours: 60 hRecommended self-study hours: 100 h
Course literature
Additional literature
Books
- Shoham, Yoav and Leyton-Brown, Kevin, (2009) Multiagent systems - Algorithmic, Game-Theoretic and Logical Foundations Cambridge University Press
ISBN: 978-0-521-89943-7
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| UPG1 | Assignments | 4 credits | U, 3, 4, 5 |
| LAB1 | Laboratory work | 2 credits | U, G |
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.
Additional literature
Books
Shoham, Yoav and Leyton-Brown, Kevin, (2009) Multiagent systems - Algorithmic, Game-Theoretic and Logical Foundations Cambridge University Press
ISBN: 978-0-521-89943-7
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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| 1.2 Fundamental engineering knowledge (G1X level) |
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X
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LAB1
UPG1
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
X
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X
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LAB1
UPG1
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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 |
|
X
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X
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LAB1
UPG1
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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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X
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X
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| 2.4 Attitudes, thought, and learning |
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X
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X
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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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| 3.2 Communications |
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X
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| 3.3 Communication in foreign languages |
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X
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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 |
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X
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| 4.4 Designing |
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X
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| 4.5 Implementing |
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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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