Monday, February 28, 2011

The Business Assessment Model

The Business Assessment Model (BAM) evaluates trajectories of People, Performance and Planet (3P) of a single company as well as of the whole market system as a function of business decision of actors, exogenous events in the broader socioeconomic environment or both.

BAM computes the cumulative di difference between predictions of the perturbed and original 3P trajectories in order to conduct analysis of decisions within the medium run planning horizon.





Figure: Integrated 3P trajectories comparing system-level dynamics of both Baseline and Variant scenarios

Who is behind BAM?


This project has been developed by Robert Axtell and Maciej Latek from the Department of Computational Social Science, at George Mason University and Francesco Cordaro from Mars Corporation. Funding has been provided by Mars Inc. through it's Economics of Mutality initiative.

Where can I see BAM?

The project website https://www.assembla.com/wiki/show/sweetmutuality/ on which you can:
  • Read an early working paper (pdf, 13 pages);
  • Download self contained, ready to run version of the BAM simulation used in the "Comprehensive Assessment of Businesss Decisions" working paper (zip file) and associated presentation (ppt file) on running and interpreting outputs;
  • See Validation Verification experiments we have performed with the current revision of the BAM, not included in the working paper;
BAM is implemented in MASON simulation framework.

Wednesday, February 09, 2011

Summer Course - Decision Maker Short Course - Computational Social Science & Policy

The Krasnow Institute at George Mason University is offering a Computational Social Science & Policy short course from June 19 - Jun 24, 2011. Click here to see more details.

The course description is as follows:

This six-day, non-credit, course is a unique opportunity to work with a team of experienced computational social scientists to explore and understand the application of new interdisciplinary approaches to modeling and making decisions involving the operations of social systems. Participants will imerse themselves in an intensive tour of the field of Computational Social Science, a broad set of efforts that seek to explain and predict how large-scale human systems from organizations to urban systems, from economies to society as a whole, evolve, react to stresses and stimuli, and cooperate and compete. Participants will hear presentations from experts in the field and engage in intensive dialoguing, demonstrations, and policy scenarios.

For further information and details see: http://krasnow.gmu.edu/DMSC/dmsc-css.html

Computational Social Science Concentration in the Master of Arts in Interdisciplinary Studies

We have recently received approval for a Master of Arts in Interdisciplinary Studies MAIS with a concentration in Computational Social Science starting in the Fall of 2011. Click here to to see the full details or read below.

Computational Social Science (CSS) is a relatively new interdisciplinary science in which social science questions are investigated with modern computational tools. Computational social scientists investigate complex social phenomenon such as economic markets, traffic control, and political systems by simulating the interactions of the many actors in such systems, on computers. They hope to gain insights which will lead to better management of the behavior of the larger social systems, i.e., prevention of market crashes, smoothed traffic flow, or maintenance of political stability. The intractability of many social problems calls for the new approaches provided by computational social science.

CSS is a highly interdisciplinary field that requires teams to plan and complete projects, be they undertaken by government, industry, or non-profit entities. Project managers of such teams, overseeing all elements of project design and execution, tend to hold PhDs. The MAIS concentration will train students to be members of these project teams, able to meaningfully contribute to background research and to project design, execution, and communication.

Prior background should include a bachelor’s degree in one of the social sciences, in computer science, in engineering, or in a relevant discipline, as well as undergraduate courses in these and related areas. Bachelor’s degrees in other areas are also eligible, but the student may be required to take additional courses in social science, mathematics, or computer science as prerequisites to admission.

This concentration will be available in fall 2011.

Concentration Requirements (Catalog Year 2010-2011)

  • Six core courses (18 credits)

  • Three required courses (9 credits): CSS 600, 605, 610

    The required CSS courses provide an understanding of the conceptual, technical, and practical foundations of computational social science.

  • Three elective courses (9 credits) chosen from: CSS 620, 625, 645, 692, 739

    The electives provide an understanding of the technical foundations and current work in at least two subfields of computational social science.

  • One research courses (3 credits) chosen from: CSS 796, 898, 899

    The research course provides students with exposure to the most current ongoing research in the field and allows them to further develop their computational research expertise.

  • Three-four elective courses (9-12 credits)

    The electives allow students to acquire a substantive specialization as well as additional training in social and computational science. Because of the broad spectrum of social science phenomena, methodologies, and student backgrounds, there is a large pool of potential courses. Electives may include any Mason master’s-level course in computational social science, social science, computer science, statistics, or other quantitative methods such as data visualization, information technology, and geographic information science. Electives should be selected in conjunction with and approval of the student’s advisor and the Director of CSS Graduate Studies. If the student does not have prior coursework in multivariate statistical analysis, the electives should include at least one such course relevant for the student’s chosen specialization.

    Students who elect to do a 5-credit project or a thesis take 9 elective credits. Students who do a 2-credit project take 12 credits.

  • Proposal (1 credit): MAIS 797

  • Project (2-5 credits) or thesis (5 credits): MAIS 798 or MAIS 799.

Total: 36 Credits

Requirements may be different for earlier catalog years. See the University Catalog archives.

Director
Claire Snyder-Hall
mais@gmu.edu

Contact information
Robert Axtell
Head of the Concentration in Computational Social Science

Contact: Karen Underwood
Academic Department Coordinator
Department of Computational Social Science
Research 1, Room 373, MSN 6B2
Fairfax, VA 22030
703-993-9298
cssgrad@gmu.edu