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EKO 324 | Decision Making and Game Theory | 3+0+0 | ECTS:5 | Year / Semester | Spring Semester | Level of Course | First Cycle | Status | Compulsory | Department | DEPARTMENT of ECONOMETRICS | Prerequisites and co-requisites | None | Mode of Delivery | Face to face | Contact Hours | 14 weeks - 3 hours of lectures per week | Lecturer | Prof. Dr. Tuba YAKICI AYAN | Co-Lecturer | None | Language of instruction | Turkish | Professional practise ( internship ) | None | | The aim of the course: | This course aims to enhance the students' ability to think strategically in complex interactive environments and to provide them with an understanding of the use decision and risk analysis for evaluation of real world projects and opportunities |
Learning Outcomes | CTPO | TOA | Upon successful completion of the course, the students will be able to : | | | LO - 1 : | determine numerical methods which can be used to make choice among multiple alternatives. | 1,2,3,4,5,6,7 | 1 | LO - 2 : | define similar and different features of decision making methods | 1,2,3,4,5,6,7 | 1 | LO - 3 : | solve decision making problems by means of learned methods. | 1,2,3,4,5,6,7 | 1 | LO - 4 : | select best fit method for decision environment | 1,2,3,4,5,6,7 | 1 | LO - 5 : | make the right decision by means of learned methods | 1,2,3,4,5,6,7 | 1 | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | |
Decision making under uncertainty : The maximin criterion, the maximax criterion, the Laplace criterion, the Hurwitz criterion, the savage criterionDecision rules in risk environment: The maximum possibility criterion, the expected minimum opportunity cost, value of experimentationDecision trees : Drawing a decision tree, evaluating the decision tree, calculating the tree values, calculating the value of uncertain outcome nodes, calculating the value of decision nodes, making decisionGame theory: The formulation of two-person, zero-sum games, solving simple games, games with mixed strategies, graphical solution procedure, solving by linear programming. Queuing theory: Basic structure of queuing models, queuing models involving exponential distribution, queuing models based on the birth-death process, queuing models involving nonexponential distributions, queuing networks. |
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Course Syllabus | Week | Subject | Related Notes / Files | Week 1 | Course objectives and outlines | | Week 2 | Decision making under uncertainty : The maximin criterion, the maximax criterion, the Laplace criterion, the Hurwitz criterion, the savage criterion | | Week 3 | Decision rules in risk environment: The maximum possibility criterion, the expected minimum opportunity cost, value of experimentation | | Week 4 | Decision trees : Drawing a decision tree, evaluating the decision tree, calculating the tree values, calculating the value of uncertain outcome nodes, calculating the value of decision nodes, making decision | | Week 5 | Game theory: The formulation of two-person, zero-sum games, solving simple games, games with mixed strategies | | Week 6 | Graphical solution procedure | | Week 7 | Solving by linear programming | | Week 8 | Queuing theory: Basic structure of queuing models | | Week 9 | Mid-term exam | | Week 10 | Queuing models involving exponential distribution, queuing models based on the birth-death process | | Week 11 | Queuing models involving nonexponential distributions | | Week 12 | Queuing networks, single server queuing models | | Week 13 | Multiple server queuing models | | Week 14 | Exercises about waiting lines | | Week 15 | Review | | Week 16 | End-of-term exam | | |
1 | Clemen, R. , Reilly, T. , 2004, Making Hard Decisions with Decision Tools Suite, 1st ed, Duxbury Pres. | | |
1 | Hillier, F. , Liberman, G. , 2005, Introduction to Operations Research, 8 st ed. , Mc Graw-Hill Science. | | 2 | Neumann, J. , Morgenstern, O. , 2004, Theory of Games and Economics Behavior, 16th ed. , Princeton University Press. | | |
Method of Assessment | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | Mid-term exam | 9 | 04/2016 | 1 | 50 | End-of-term exam | 16 | 05/2016 | 1 | 50 | |
Student Work Load and its Distribution | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | Yüz yüze eğitim | 3 | 14 | 42 | Sınıf dışı çalışma | 4 | 14 | 56 | Arasınav için hazırlık | 8 | 2 | 16 | Arasınav | 1 | 1 | 1 | Ödev | 1 | 1 | 1 | Dönem sonu sınavı için hazırlık | 11 | 3 | 33 | Dönem sonu sınavı | 1 | 1 | 1 | Total work load | | | 150 |
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