Center for Social Complexity

Category: News and Events

Dr. Robert Axtell Friday Speaker

Dr. Robert Axtell, Professor, Computational Social Science Program, Department of Computational and Data Sciences, College of Science/Department of Economics, College of Humanities and Social Sciences, George Mason University, will be the speaker at the Computational Social Science Research Colloquium/Colloquium in Computational and Data Sciences speaker on Friday, September 28. Dr. Axtell’s talk entitled “Are Cities Agglomerations of People or of Firms? Data and a Model” (abstract below) will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the newly created CSS program YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

ABSTRACT: Business firms are not uniformly distributed over space. In every country there are large swaths of land on which there are very few or no firms, coexisting with relatively small areas on which large numbers of businesses are located—these are the cities. Since the dawn of civilization the earliest cities have husbanded a variety of business activities. Indeed, often the raison d’etre for the growth of villages into towns and then into cities was the presence of weekly markets and fairs facilitating the exchange of goods. City theorists of today tend to see cities as amalgams of people, housing, jobs, transportation, specialized skills, congestion, patents, pollution, and so on, with the role of firms demoted to merely providing jobs and wages. Reciprocally, very little of the conventional theory of the firm is grounded in the fact that most firms are located in space, generally, and in cities, specifically. Consider the well-known facts that both firm and city sizes are approximately Zipf distributed. Is it merely a coincidence that the same extreme size distribution approximately describes firm and cities? Or is it the case that skew firm sizes create skew city sizes? Perhaps it is the other way round, that skew cities permit skew firms to arise? Or is it something more intertwined and complex, the coevolution of firm and city sizes, some kind of dialectical interplay of people working in companies doing business in cities? If firm sizes were not heavy-tailed, but followed an exponential distribution instead, say, could giant cities still exist? Or if cities were not so varied in size, as they were not, apparently, in feudal times, would firm sizes be significantly attenuated? In this talk I develop the empirical foundations of this puzzle, one that has been little emphasized in the extant literatures on firms and cities, probably because these are, for the most part, distinct literatures. I then go on to describe a model of individual people (agents) who arrange themselves into both firms and cities in approximate agreement with U.S. data.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

CDS’s Michael Eagle 9/21 speaker

The Computational Social Science Research Colloquium /Colloquium in Computational and Data Sciences speaker for Friday, September 21 will be Michael Eagle, Asst. Professor, Computational and Data Sciences, College of Science. Dr. Eagle’s talk is scheduled to begin at 3:00 in the Center for Social Complexity suite located on the 3rd floor of Research Hall. His talk will be followed by a Q&A session along with light refreshments.

Some of Dr. Eagle’s publication topics include:

Predicting Individual Differences for Learner Modeling in Intelligent Tutors from Previous Learner Activities
Measuring Gameplay Affordances of User-Generated Content in an Educational Game
Estimating Individual Differences for Student Modeling in Intelligent Tutors from Reading and Pretest Data
Using game analytics to evaluate puzzle design and level progression in a serious game
Measuring Implicit Science Learning with Networks of Player-Game Interactions
Exploration of Student’s Use of Rule Application References in a Propositional Logic Tutor An Algorithm for Reducing the Complexity of Interaction Networks
Evaluation of Automatically Generated Hint Feedback
Exploring Player Behavior with Visual Analytics InVis: An Interactive Visualization Tool for Exploring Interaction Networks

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

CORRECTION: William Kennedy, PhD, Captain, USN (Ret.), featured on 9/14 seminar

The Computational Social Science Research Colloquium /Colloquium in Computational and Data Sciences speaker for Friday, September 21, will be William Kennedy, PhD, Captain, USN (Ret.), Research Assistant Professor, Center for Social Complexity, Computational and Data Sciences, College of Science. Dr. Kennedy’s talk entitled “Characterizing the Reaction of the Population of NYC to a Nuclear WMD” (abstract below) will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

We hope to see you on Friday, September 21st.

Abstract: This talk will review our status two years into our multi-year project to characterize the reaction of the population of a US megacity to a nuclear WMD event. Our approach has been to develop an agent-based model of the New York City area, with agents representing each of the 23 million people, and establish a baseline of normal behaviors before exploring the population’s reactions to small (5-10Kt) nuclear weapon explosions. We have modeled the environment, agents, and their interactions, but there have been some challenges in the last year. I’ll review our successes and challenges as well as near-term plans.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

Laidlaw Scholar Kieran Marray opens fall colloquium series

Welcome back everyone!

The opening colloquium speaker for the fall semester is Kieran Marray. Kieran is a Laidlaw Scholar from St Catherine’s College, University of Oxford. He has been visiting the Center for Social Complexity over the summer to do research in complexity economics supervised by Professor Rob Axtell.

Kieran’s talk entitled “FORTEC: Forecasting the Development of Artificial Intelligence up to 2050 Using Agent-Based Modelling” (abstract follows) is scheduled for 3:00 p.m. on Friday, August 31, in the Center for Social Complexity suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the newly created CSS program YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

We hope to see you on Friday, August 31.

FORTEC: Forecasting the Development of Artificial Intelligence up to 2050 Using Agent-Based Modeling

The past decade has been characterised by massive leaps forward in fields like machine learning and computer vision. Will it last? How should we think about this problem? I shall argue that agent-based modelling can be used to forecast the emergence of innovation in AI and should be able to do so better than the current models. I shall do this as follows. Firstly, I shall review previous attempts, specifically Osborne and Frey (2013) and McKinsey (2017). However, I shall show that the methodology underlying these approaches is flawed due to its reliance upon expert opinion. This can be reduced by simulating the individual firms and their actions in an empirically realistic manner. So, I shall attempt to do this, building an agent-based forecasting model (FORTEC) from the bottom up. It will be applied to the set of firms and research labs in the US working on AI to derive the first empirical predictions for the ability to automate nineteen different types of task from now until 2050. The model is far from perfect, though; it is intended simply as a first approximation for others to build upon. Therefore, I shall finish by laying out some ways in which this framework could be applied or improved, from forecasting innovations in other high-technology industries such as photovoltaics to simulating non-American firms.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

“Modeling Panic with Psychological Agents”

CSS Seminar

Friday, May 4, 2018

Center for Social Complexity Suite located on the 3rd floor of Research Hall

3:00 pm

Final Seminar of Semester. Program Will Recommence in Fall 2018.

Sanjay Nayar, CSS PhD student, will present “Modeling Panic with Psychological Agents” (abstract below) in this Friday’s CSS seminar. The talk will be followed by a Q&A session along with light refreshments.

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

Abstract: Agent-Based Modeling (ABM) is steadily gaining traction in the modeling of real-world financial models built/used by organizations such as the Office of Financial Research, IMF, European Central Bank and others. As expected, the models are starting to show more complexity over the years but still lack much detailed modeling of agents at a psychological level. This becomes especially important in a crisis as individuals panic and make emotional decisions that are far from being fully rational or perhaps even boundedly-rational, in the traditional definition of the term. This exploratory talk will cover some of the recent ABM efforts in modeling financial crises and discuss the possible design elements for implementing and enhancing the psychological modeling of individuals agents, focusing on panic behavior in highly stressful/disastrous situations. Similarities and differences between financial panic and pedestrian/evacuation panic models will also be discussed, along with underlying theories of panic such as panics of “escape” and panics of “affiliation.”

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

Elaine Reed, PhD, MITRE Corporation, to be seminar speaker

Friday, April 27
Center for Social Complexity
3rd floor Research Hall
3pm

The CSS seminar speaker for Friday, April 27th, will be Elaine Reed, PhD, PMP from The MITRE Corporation. Dr. Reed’s talk is entitled “The Emergence of Self-governance Institutions: Agent-based Simulation of Game Theoretic Models of Democratization” (abstract below). The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the newly created <a href="https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA
CSS program YouTube channel . For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit our calendar.

Abstract: My work developed an agent based simulation of Acemoglu and Robinson’s game theoretic models to explore the incentives and interactions that lead to the creation and consolidation of democracy. A growing body of work has found that the way a society organizes itself through its political institutions impacts its economic performance. This work has been largely descriptive. Empirical work has focused on highly aggregate country level characteristics and no description of the underlying human motivations and mechanisms.

Institutions are created by people interacting in complex ways with others in their socio-economic environment. A study of institutions should therefore study the people and interactions that create them. Acemoglu and Robinson developed a theory on the creation and consolidation of democracy through a game-theoretic framework. They studied how economic incentives influence the way social groups shape institutions to allocate political and economic power. The A&R models assume groups of people are completely rational and identical intra-group in order to make the models mathematically tractable. My dissertation utilizes an agent-based computational methodology to reproduce the A&R formal models with the same restrictions in order to validate my model. Specifically, with intra-group homogeneity the agent-based model reproduces the group-level threshold conditions affecting institutional choices found by A&R. I show that these results are robust to parameter changes within the ranges defined by A&R. The more flexible computational methodology allows me to relax the restrictive assumptions and explore how a more realistic set of assumptions such as heterogeneous incomes and limited intelligence affect the larger outcomes for all groups. The population structure with heterogeneity can include a more realistic middle class. Modeling a middle class by using agent-based models with heterogeneous agents finds that the effect of a middle class is non-linear and does not make democratizations more likely for all ranges of underlying economic conditions. This work demonstrates the usefulness of agent-based modeling as a viable alternative quantitative methodology for studying complex institutions.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

A Proof of Concept: An Agent-Based Model of Colorism within an Organizational Context (Local Policing)

CSS seminar
Friday, April 20th
3pm, Center for Social Complexity Suite located on the 3rd floor of Research Hall

Henry Smart, III, Ph.D. Candidate, Virginia Tech, will present “A Proof of Concept: An Agent-Based Model of Colorism within an Organizational Context (Local Policing)” (abstract below). The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the newly created CSS program YouTube channel.
For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/ For a list of upcoming and previous seminars, please visit our calendar.

Abstract: Colorism is the allocation of privilege and disadvantage based on skin color, with a prejudice for lighter skin. This project uses agent-based modeling (computational simulation) to explore the potential effects of colorism on local policing. I argue that colorism might help to explain some of the racial disparities in the United States’ criminal justice system. I use simulated scenarios to explore the plausibility of this notion in the form of two questions: 1) How might colorism function within an organization; and 2) What might occur when managers apply the typical dilemmatic responses to detected colorism? The simulated world consists of three citizen-groups (lights, mediums, and darks), five policy responses to detected colorism, and two policing behaviors (fair and biased). Using NetLogo, one hundred simulations were conducted for each policy response and analyzed using one-way ANOVA and pairwise comparison of means. When the tenets of colorism were applied to an organizational setting, only some of the tenets held true. For instance, those in the middle of the skin color spectrum experienced higher rates incarceration when aggressive steps were taken to counter colorism, which ran counter to the expectations of the thought experiment. The study identified an opportunity to expand the description of colorism to help describe the plight of those in the middle of the skin color spectrum. The major contributions from this work include a conceptual model that describes the relationship between the distinct levels of colorism and it progresses the notion of interactive colorism. The study also produced conditional statements that can be converted into hypotheses for future experiments.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

4/13: “Hype and Conquer: A Computational Model about Winning in the Platform Wars”

CSS Seminar
Friday, April 13
3-4pm
Center for Social Complexity/3rd floor Research Hall

The CSS seminar speaker for Friday, April 13th will be André L’Huillier, CSS PhD Candidate. André’s talk is entitled “Hype and Conquer: A Computational Model about Winning in the Platform Wars” (abstract below). The talk will be followed by a Q&A session along with light refreshments.

Abstract: Platform business models like Ali-Baba or Google are disrupting many industries while displaying a “winner-takes-all” behavior. The disruption has been increasing during the last decade thanks to the digital revolution. Although the digital transition is relatively new and is catalyzing the creation of platform markets, it is not new for the video game market. The game industry has dealt with platform dynamics since its very beginnings during the mid 70’s. This long history allows the study of its overall life cycle and the individual cycles of platform generations (a set of competing platforms with similar technology), and specific platforms or games. Understanding how a blockbuster emerges in the market provides insight into the behavior of current and near-future developments of platforms. Uneven competition and its volatility of multi-sided organization have captured the attention of economists and entrepreneurs; specifically, they have focused on the “launching problem” and achieving critical mass adoption. Depending on the goods and services, uncertainty on a product’s performance may force actors to prioritize indicators such as trust and perceived quality. In the case of the video game industry, producers and consumers actions lead towards a “winner-takes-all” or “winner-takes-most” structure. Within the video game market, only a handful of consoles and games emerge as blockbusters and sustain cultural and financial dominance. I will present a computational model that portrays the home console industry as a multi-sided market based on platform economics and individual level social influence and decision making. A rule-based model is presented to reproduce the main behavior of different heterogeneous actors, allowing to understand the moving parts of platforms’ blockbuster emergence. The model studies the influence of mass media and peer-to-peer information in platform and software adoption; focusing on the networked diffusion of information and indirect network effects of actors’ decisions.

This session will be live-streamed on the newly created CSS program YouTube channel. For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group.

For a list of upcoming and previous seminars, please visit our calendar.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

Chief Analytics Officer, Office of Naval Research, Dr. Ryan Zelnio

Friday, March 23
3pm
Center for Social Complexity

The CSS seminar speaker for Friday, March 23 will be Ryan Zelnio, Ph.D., Chief Analytics Officer, Office of Naval Research. Dr. Zelnio’s talk entitled “The Creation of the Office of Naval Research’s Data & Analytics Lab” (abstract below) is scheduled to begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

Abstract: The Office of Naval Research (ONR) coordinates, executes, and promotes the science and technology programs of the United States Navy and Marine Corps. It administers the Naval Research Enterprise (NRE) investment portfolio of $2B annually in Naval relevant science and technologies (S&T) ranging from basic research to technology prototyping. This portfolio covers over 3000 grant and contract awards annually over a large variety of technologies. In FY2017 alone, the basic and applied research portfolio (which is less than 50% of its budget) funded 4,411 scientific articles, 2,732 conference papers, 343 theses, 204 books & book chapters and 88 patents. However, while this portfolio is large, it is a drop in the bucket within the global research & development (R&D) enterprise. In an attempt to understand this vast amount of data being produced both within the NRE and globally, ONR recently stood up the Data & Analytics Lab. Its mission is to support strategic decision making at the Office of Naval Research with in-depth analysis of the NRE portfolio to enhance mission effectiveness for U.S. Naval Forces. This new lab is led by Mr. Matt Poe and includes Dr. Ryan Zelnio (2013 GMU SPP grad) serving as the Chief Analytics Officer and LCDR Nick Benes serving as the Chief Data Officer. This lab seeks to harness ONR’s investments in social network analysis, machine learning, natural language processing, data visualization, supervised and unsupervised clustering, and many other data science tools to support decision processes across the NRE. Their talk will cover the range of challenges facing their lab as they stand up their effort and discuss the broader move within the federal government to better apply the tools of data science to understand the complexity of the R&D enterprise. They will also discuss future partnering and internship opportunities.

For a list of upcoming and previous seminars, please visit our calendar.

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.

Drafting Agent-Based Modeling Into Basketball Analytics

The CSS seminar speaker for Friday, February 9 will be Matthew Oldham, CSS PhD Student, Department of Computational and Data Sciences. The program will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the newly created CSS program YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

We hope to see you on Friday, February 9.

Abstract: Sports analytics (SA) has experienced a meteoritic rise in recent years, with the trend forecast to continue. Modor Intelligence reports that the market was valued at USD 83.56 million in 2015, and is forecast to grow to USD 447.23 million by 2020. at the market was valued at USD 83.56 million in 2015, and is forecast to grow to USD 447.23 million by 2020.

The growth of sports analytics has raised a rich variety of research topics pertaining to basketball, including: how at the macro level the distribution of scoring activity is a mixture of random walk processes and power-law behavior (Gabel & Redner, 2012), and, at the individual level, the question of whether players develop hot-hands and how the player and their teammates react to its possible existence. While the erroneous belief regarding hot-hands was first identified by Gilovich, Vallone & Tversky (1985) it has remained an active field of research (Bar-Eli, Avugos, & Raab, 2006).

Agent-based modeling (ABM) has great potential to assist and inform those engaged in sports analytics but to date it has not been utilized. The advantage of ABM is that it allows researchers to assess, in a silicon laboratory, the micro-level interactions that give rise to verifiable macro outcomes. This is achieved through heterogeneous agents adapting and making decisions based on their environment, including considering spatial, temporal factors and interactions with other agents.

To support the use of ABM in sports analytics, I will present a 3-dimensional model of a basketball game, where the fundamentals of play including player and court positions, a shot clock, and shooting performance are all included. Additionally, player behavior in deciding whether to shoot, pass or dribble is partially predicated on assessing the length of a player’s shooting streak (designed to test the hot-hand effect), and the consideration they give to any streak, plus their franchise status, a feature identified in Burns (2004). The probabilistic nature of the model allows for insights into the dynamics of scoring actions following a random walk. The model captures extensive data which was used to calibrate and validate it against comparable statistics from the National Basketball Association (NBA).

  • *The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.