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HU Credits:
2
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Geography
Semester:
1st Semester
Teaching Languages:
Hebrew
Campus:
Mt. Scopus
Course/Module Coordinator:
Dr. Yair Grinberger
Coordinator Office Hours:
Tuesday 13:00-14:00, Room 4622, Social Sciences faculty
Teaching Staff:
Dr. Asher Yair Grinberger
Course/Module description:
This course presents simulations as a tool for urban research and planning, focusing on agent based models. In the course, we will discuss various types of simulations and models, the theoretical foundation of urban simulations and the methodological questions one needs to consider when designing a simulation model. This theoretical knowledge will be brought into practice in exercises in which we will learn how to program models and run simulations in python.
Course/Module aims:
This course has two objectives:
1. Conveying the theoretical and methodological knowledge required for designing an urban model and interpreting the results of a simulation.
2. Conveying the practical knowledge required for programming a model, running simulation, and creating outputs.
Learning outcomes - On successful completion of this module, students should be able to:
* To explain when and for what purposes one can use an urban simulation
* To describe the steps and considerations required when designing an urban simulation
* To define sensitivity and validity tests for a model
* To program intelligent agents in Python
* To represent the urban environment in a Python code
* To produce visual and tabular outputs for simulations
* To analyze the results of a simulation
Attendance requirements(%):
Teaching arrangement and method of instruction:
Theoretical frontal lectures and practical exercises
Course/Module Content:
* What is an urban model?
* Approaches for modeling the urban system
* Agent-based models
* Decision and behavior rules in a model
* Representing the urban environment in a model
* Adaptation and learning among agents
* Analyzing and visualizing results
* Model calibration and validation
* Model development using matrix calculations
* Theoretical considerations and practices in designing a good model
Required Reading:
No required reading is defined for the course. A recommended literature list will be available in the course's webpage
Additional Reading Material:
Course/Module evaluation:
End of year written/oral examination 0 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 50 %
Assignments 40 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 10 %
Completing quizzes in the course's webpag
Additional information:
Course requirements:
Submitting 4 exercises, completing short online quizzes following lectures, and submitting a project.
You are allowed to submit the exercises and the project in pairs.
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