2024/2025 KAN-CDSCV1002U Game Theory for Business and Data-driven Decision Making
English Title | |
Game Theory for Business and Data-driven Decision Making |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Full Degree Master |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 60 |
Study board |
Master of Science (MSc) in Business Administration and Data
Science
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 12-11-2024 |
Relevant links |
Learning objectives | ||||||||||||||||||||||||||||
To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors:
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Course prerequisites | ||||||||||||||||||||||||||||
The course has no prerequisites except that the students should know the basic mathematics. Also, course requires an interest in and commitment to learn and acquire necessary skills to understand the concepts of game theory and hands-on exercises. However, no prior coding experience or knowledge about game theory is required. | ||||||||||||||||||||||||||||
Prerequisites for registering for the exam (activities during the teaching period) | ||||||||||||||||||||||||||||
Number of compulsory
activities which must be approved (see section 13 of the Programme
Regulations): 2
Compulsory home
assignments
Each student has to get 2 out of 3 activities approved in order to qualify for the final exam. There are three group reports of max. 5 pages written in groups of 2-4 students. Each team will be provided with written feedback on the reports. Each report forms the foundation of a part of the final report. This ensures the students will understand the expectations of the final before submission. There will not be any extra attempts provided to the students before the ordinary exam. If a student cannot participate in the compulsory activities due to documented illness, or if a student does not have the activities approved in spite of making a real attempt, then the student will be given one extra attempt before the re-exam: one home assignment (max.10 pages) which will cover 2 mandatory activities. |
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Examination | ||||||||||||||||||||||||||||
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Course content, structure and pedagogical approach | ||||||||||||||||||||||||||||
Game theory has applications in numerous fields, such as computer science, economics, social science and political science. Game theory is also now finding its applications in data-driven decision-making. Many business decisions can be modelled and analysed using game theory.
This course aims to provide a basic understanding of various game-theoretic concepts and their application in different application areas. In this course, basic tools of game theoretic analysis will be introduced, and we will outline some of the applications of game theory, primarily in business and economics domains, such as market competition, auctions, and bargaining. We will also cover some advanced applications such as game theory for Artificial Intelligence, Sustainable business, Climate change etc.
The course will cover different types of games as listed below:
All the games will be covered with practical examples and their applicability to different scenarios.
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Description of the teaching methods | ||||||||||||||||||||||||||||
The class is a mixture of recorded lectures,
other online activities, face to face lecture/discussion sessions,
and practical exercises in a hands-on session.
The lectures will be combined with some pragmatic hands-on exercises using various software tools such as GAMBIT, Game Theory Explorer (GTE) etc. for game theory. For some of the lectures, additional lecture notes will be provided by the teacher. |
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Feedback during the teaching period | ||||||||||||||||||||||||||||
As part of the mandatory assignment, students
will have to submit reports of max. 5 pages written in groups of
2-4 students. Each group will get feedback on the written product.
In addition to that there will be hands-on exercise as part of
exercises session in the classroom.
Students periodically are presented with online quizzes where they receive automatic feedback on their responses. The instructor also has weekly office hours where the students can get feedback of various forms, including followup on their weekly activity sessions, clarification and discussion of weekly readings and lectures, and discussion of plans for course project. Students receive feedback on their plans for final project. |
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Student workload | ||||||||||||||||||||||||||||
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Expected literature | ||||||||||||||||||||||||||||
The literature will be shared via Canvas before the semester starts. Students are advised to check the syllabus on Canvas before buying any material.
Books and Scientific Articles
Hand-on exercises
Some suggested text books and research articles for reference:
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