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[转载]资讯 | “面向社会科学家的Agent建模”BEHAVE(线上)暑期学校
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随着近年来计算社会科学研究的兴起，以计算机仿真、复杂网络分析、大数据分析等为代表的一系列新兴科学研究方法的应用普及极大地拓宽了学者们的研究视野，为分析和研究人类社会、经济、组织管理的复杂行为模式提供了十分重要的方法论和技术手段。意大利米兰大学BEHAVE实验室长期举办Agent建模与计算社会科学主题系列国际暑期学校项目。受当前新冠肺炎疫情影响，BEHAVE Summer School 2021 将于今年8月30日至9月10日线上举行。
BEHAVE Online Summer School 2021 on “Agent-Based Modelling for Social Scientists”, 30 August-10 September
Jointly organised by Behave Lab, ESSA-European Social Simulation Association, GECS–Research Group on Experimental and Computational Sociology (University of Brescia), the ESLS PhD Programme in Economic Sociology and Labour Studies (University of Milan) and supported by Fondazione Grazioli and Collegio Universitario Luigi Lucchini di Brescia, this school aims to train students on Agent-Based Models (ABM) in NetLogo by using modelling examples from social science research.
Lectures + hands-on training with two virtual rooms in parallel for student assistance
The first course addressed to beginner or experts needing a refresh, the second to advanced training on model calibration and ouput statistical analysis, with an intermediate sunday tutorial on R for beginners.
Some classic ABMs will be coded from scratch in NetLogo. No previous coding skills required during the first course.
Assistance and customized counselling on personal research projects during the course with leading experts.
Personal project presentations.
Students will be provided with the theoretical background on the use of ABM in social science research and will learn how to develop an ABM from scratch. No prerequisite on computing is needed. Students will be connected via ZOOM and will be trained with their own laptop. Students are also encouraged to develop a customized project starting from a personal research idea: bring your own model or data if you have, and we will help you! During the advanced course, students will be trained on empirical calibration of parameters with quantitative and qualitative data, validation techniques and model documentation. The last slot of the advanced training will include a session on how to survive peer review and editors when trying to publish ABM studies in scholarly journals.
Federico Bianchi (University of Milan, Italy)
Tatiana Filatova (Delft University of Technology, Delft, Netherlands)
Simone Gabbriellini (University of Trento, Italy)
Gianluca Manzo (CNRS and Sorbonne University, Paris, France)
Nicolas Payette (University of Oxford, United Kingdom)
Flaminio Squazzoni (University of Milan, Italy, School director)
Introductory course 入门班课程：
| Introductory Course | |||||
|---|---|---|---|---|---|
| Monday, 30 August 2021 | Tuesday, 31 August 2021 | Wednesday, 1 September 2021 | Thursday, 2 September 2021 | Friday, 3 September 2021 | |
| 9:30AM-10:AM | Welcome | ||||
| 10AM-11AM | The Theory and Methodology of Agent-Based Modelling (Flaminio Squazzoni, University of Milan). This lecture provides an introduction to the application of agent-based modelling in the social sciences. | From theory to coding (Simone Gabbriellini, University of Trento). This lecture introduces students to ABM thinking and modelling philosophy. The focus is on how to move from a variable-based to an agent-based modelling approach | Axelrod’s (1997) model on the dissemination of culture in NetLogo (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Flache and Macy (2011)’s model on small world and cultural polarization (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Student presentations |
| 11:15-12:30PM | The Theory and Methodology of Agent-Based Modelling (Flaminio Squazzoni, University of Milan). This lecture provides an introduction to the application of agent-based modelling in the social sciences. | Introduction to NetLogo (Nicolas Payette, University of Oxford). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Axelrod’s (1997) model on the dissemination of culture in NetLogo (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Flache and Macy (2011)’s model on small world and cultural polarization (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Student presentations |
| 2-3:30PM | Agents and Interactions: The Crux of the ABM Matter (Flaminio Squazzoni & Federico Bianchi, University of Milan). This lecture provides an overview of the most important theoretical challenges when designing ABM. | Introduction to NetLogo (Nicolas Payette, University of Oxford). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Axelrod’s (1997) model on the dissemination of culture in NetLogo (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Flache and Macy (2011)’s model on small world and cultural polarization (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | ABM standards (Flaminio Squazzoni, University of Milan) |
| 3:45-16:45PM | The State-of-the-Art (Federico Bianchi, University of Milan). This lecture summarises the main achievement of ABM research in the social science. | Schelling’s Segregation Model in NetLogo (Nicolas Payette, University of Oxford). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Axelrod’s (1997) model on the dissemination of culture in NetLogo (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | Flache and Macy (2011)’s model on small world and cultural polarization (Simone Gabbriellini, University of Trento). This lecture uses a canonical model to train students on agent-based modelling in NetLogo | ABM standards (Flaminio Squazzoni, University of Milan) |
| 5-6PM | Counselling. The faculty will help students to define and develop their model by concentrating either on ABM research questions/simulation design strategies or specific modelling details | Counselling. The faculty will help students to define and develop their model by concentrating either on ABM research questions/simulation design strategies or specific modelling details | Counselling. The faculty will help students to define and develop their model by concentrating either on ABM research questions/simulation design strategies or specific modelling details | Counselling. The faculty will help students to define and develop their model by concentrating either on ABM research questions/simulation design strategies or specific modelling details | Closing |
Advanced course 高级班课程：
| Advanced Course | |||||
|---|---|---|---|---|---|
| Monday, 6 September 2021 | Tuesday, 7 September 2021 | Wednesday, 8 September 2021 | Thursday, 9 September 2021 | Friday, 10 September 2021 | |
| 9:30AM-10:AM | Welcome | ||||
| 10AM-11AM | Social Networks and ABMs (Gianluca Manzo, CNRS Sorbonne University, Paris, France). It is widely known that the specific way in which social ties are connected can dramatically modify how far and fast ideas and behaviors diffuse within social groups. The same holds for diseases traveling through networks of close-range physical contacts. The lecture explains how nationally representative survey data on self-reported daily contacts can be used to build empirically-calibrated agent-based models of virus propagation on complex networks. | Title TBA (Tatiana Filatova, Delft University of Technology, Delft, Netherlands) | ABM challenge – Mechanism modelling (Simone Gabbriellini, University of Trento). This lecture will help students designing hypothetical mechanisms to explain the challenge puzzle and implement them into the model | Unit testing (Nicolas Payette, University of Oxford). This lecture helps students to understand how running simulations of the coded model through NetLogo’s BehaviorSpace and terminal | Student presentations |
| 11:15-12:30PM | Social Networks and ABMs (Gianluca Manzo, CNRS Sorbonne University, Paris, France). It is widely known that the specific way in which social ties are connected can dramatically modify how far and fast ideas and behaviors diffuse within social groups. The same holds for diseases traveling through networks of close-range physical contacts. The lecture explains how nationally representative survey data on self-reported daily contacts can be used to build empirically-calibrated agent-based models of virus propagation on complex networks. | Title TBA (Tatiana Filatova, Delft University of Technology, Delft, Netherlands) | ABM challenge – Mechanism modelling (Simone Gabbriellini, University of Trento). This lecture will help students designing hypothetical mechanisms to explain the challenge puzzle and implement them into the model. | ABM challenge – Parameter sweeping (Nicolas Payette, University of Oxford). This lecture helps students to understand how running simulations of the coded model through NetLogo’s BehaviorSpace and terminal | |
| 2-3:30PM | ABM: the challenge of model calibration and validation (Flaminio Squazzoni, University of Milan, Italy). This lecture introduces students to the practices of model calibration and validation and identifies challenges and prospects. | Introduction to R and tidyverse for output analysis (Nicolas Payette, University of Oxford). This lecture introduces basic functions of the tidyverse packages for data analysis in R used for simulation output analysis | ABM challenge – Calibration | Student presentations | ABM standards and best practices (Flaminio Squazzoni, University of Milan) |
| 3:45-4:45PM | The challenge exercise (Simone Gabbriellini, University of Trento & Nicolas Payette, University of Oxford). This lecture uses a model to present a puzzle and a challenge to participants. This includes: the design of an ABM to explain an empirical puzzle on different innovation diffusion rates in two empirically-observed social networks. Students will code macro-level initial conditions of the model in NetLogo and will calibrate the model to empirical network data. Students will be familiarised with a git repository for version control of the challenge model | The challenge exercise (Simone Gabbriellini, University of Trento & Nicolas Payette, University of Oxford). This lecture uses a model to present a puzzle and a challenge to participants. This includes: the design of an ABM to explain an empirical puzzle on different innovation diffusion rates in two empirically-observed social networks. Students will code macro-level initial conditions of the model in NetLogo and will calibrate the model to empirical network data. Students will be familiarised with a git repository for version control of the challenge model | ABM challenge – Calibration | Student presentations | ABM standards and best practices (Flaminio Squazzoni, University of Milan) |
| Counselling. This slot provides students the opportunity to benefit from collective/ personalised counselling on ABM-related issues, work-in-progress research projects, coding issues. | Counselling. This slot provides students the opportunity to benefit from collective/ personalised counselling on ABM-related issues, work-in-progress research projects, coding issues. | Counselling. This slot provides students the opportunity to benefit from collective/ personalised counselling on ABM-related issues, work-in-progress research projects, coding issues. | Counselling. This slot provides students the opportunity to benefit from collective/ personalised counselling on ABM-related issues, work-in-progress research projects, coding issues. | Closing | |
Registration fee 注册费用：
Fees include: lectures, counseling, materials, videos and online infrastructure.
Fees Categories
Student fees (i.e., Bachelor, Master or PhD students): 400 euros (intro course), 600 (advanced course), 800 (full course)
Non-student, academics (i.e., post-docs, assistant, associate, full professors): 500 euros (intro course), 700 (advanced course), 900 (full course)
Non academic, professionals: 800 euros (intro course), 900 (advanced course), 1400 (full course).
To apply to the school, please send your CV and a letter of presentation describing:
the type of training you want to attend [(1) only the introductory course, (2) only the advanced course, (3) the full two weeks course]
any prior relevant expertise (e.g., ABM, R or any programming language)
the research project/objectives you are interested to develop during the school
to info@behavelab.org by 30 June 2021. Approval will be notified by 15 July 2021, after which registrations will open.
The registration form with all detail about the payment of the registration fees will be sent by email to all accepted applicants. The deadline for registration is July 31 2021. For any detail and information on the registration, please contact us here.
From: http://behavelab.org/behave-summer-school/
https://blog.sciencenet.cn/blog-286682-1285009.html
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