STPS514 AGENT BASED SIMULATION MODELS IN ECONOMICS OF TECHNOLOGICAL CHANGE
| Course Code: | 8310514 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Science and Technology Policy Studies |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Prof.Dr. ERKAN ERDİL |
| Offered Semester: | Fall or Spring Semesters. |
Course Objectives
The goal of the course is to provide a working knowledge of the concepts and methods used for cleaning and organizing data, analyzing social networks, and agent-based modeling. Their relationships with studies of innovation and complex systems shall also be introduced. By the end of the course the students will
Know the main concepts in the field of data cleaning and organizing. Implement social network analysis. Understand agent-based modeling.
Course Content
Complex adaptive systems, multi-agent simulation models, the bottom-up approach to social systems, learning and evolutionary games, genetic algorithms, agent based simulation models, network evolution.
Course Learning Outcomes
1.1 Students will organize data for data analysis by the end of the second lesson.
1.2 Students will clean data using data cleaning software at the end of the second lesson.
1.3 Student will arrange data for network analysis and agent-based modeling by the end of the second lesson.
2.2 Students will understand the basics of social network analysis techniques such as path-length, degree, clustering, centrality, etc. to examine social networks by the end of the fifth lesson.
2.3 Students will know differences among random, small-world and scale-free networks at the end of the sixth lesson.
2.4. Students will able to use social network analysis in innovation studies by the end of the ninth lesson.
2.4 Students will make social network analysis by using software at the end of the tenth lesson.
3.1 Students will know basic motivations for using agent-based modeling in innovation studies by the end of the twelfth lesson.
3.2 Students will understand the differences between rational actor and actor in agent-based model at the end of the thirteenth lesson.
3.3 Students will comprehend generative, inductive and deductive approaches at the end of the thirteenth lesson.
3.4 Students will establish an agent-based model using software by the end of the fifteenth lesson.