| Course code | CSCI5350 |
| Course title | Advanced Topics in Game Theory 博弈論高級專題 |
| Course description | This course covers fundamental concepts in game theory. The course starts with pure strategy and mixed strategy Nash equilibrium in strategic games. It then discusses some specific types of games, including zero-sum games, Bayesian games, and introduces other types of equilibriums including correlated equilibrium and evolutionary equilibrium. Extensive games, subgame perfect equilibrium, sequential equilibrium, framing effects, behavioural strategies will then be discussed. Finally, coalitional games and the core will be discussed. Advisory: Students are expected to have taken CSCI2110 or ENGG2440 or ESTR2004, ENGG2040 or ENGG2430 or ESTR2002. 本科講授博弈論的基本概念。首先討論策略博弈中的純策略和混合策略納什均衡。隨之介紹一些特別博弈，如零和博弈、貝葉斯博弈，和其他種類的均衡，包括相關均衡和演化均衡。隨之講授擴展博弈、子博弈精煉均衡、貫序均衡、設計效應、行爲策略。最後討論聯盟博奕和核心。 建議：學生應曾修讀CSCI2110或 ENGG2440或 ESTR2004, ENGG2040或ENGG2430或ESTR2002。 |
| Unit(s) | 3 |
| Course level | Postgraduate |
| Exclusion | CMSC5728 |
| Semester | 1 or 2 |
| Grading basis | Graded |
| Grade Descriptors | A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions. B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered. C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems. D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems. F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course. |
| Learning outcomes | At the end of the course of studies, students will have acquired the ability to 1. understand pure strategy and mixed strategy Nash equilibrium in strategic games; 2. understand zero-sum games, Bayesian games, correlated equilibrium and evolutionary equilibrium; 3. understand extensive games, subgame perfect equilibrium; 4. understand sequential equilibrium, framing effects, behavioural strategies, perfect Bayesian equilibrium and trembling hand perfect equilibrium. 5. understand coalitional games and the core. |
| Assessment (for reference only) |
Essay test or exam: 55% Others: 45% |
| Recommended Reading List | 1. Osborne and Rubinstein, A Course in Game Theory. The MIT Press, 1994. 2. Osborne, An Introduction to Game Theory. Oxford University Press, 2003. |
| CSCIN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. identify, formulate, and solve computer science problems (K/S); | T |
| 2. design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs (K/S); |
|
| 3. receive the broad education necessary to understand the impact of computer science solutions in a global and societal context (K/V); | T |
| 4. communicate effectively (S/V); |
T |
| 5. succeed in research or industry related to computer science (K/S/V); |
T |
| 6. have solid knowledge in computer science and engineering, including programming and languages, algorithms, theory, databases, etc. (K/S); | T |
| 7. integrate well into and contribute to the local society and the global community related to computer science (K/S/V); | |
| 8. practise high standard of professional ethics (V); | |
| 9. draw on and integrate knowledge from many related areas (K/S/V); |
T |
| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes; T = Teach; P = Practice; M = Measured | |