Welcome to the homepage for the course "Spatial Agent-based Models of Human-Environment Interactions
This site contains all the supplementary material needed for the course. Material for each class including models is given in the assigned week (click on the links to the left).
Please note that course handouts (lecture slides) will not be available until the day of the class, however core reading material and references will be provided beforehand. I do not expect you to read all the references, I provide them purely for a reference resource for topics covered in class.
You should check this website regularly for updates.
Course Syllabus (pdf
) or read below.
Spatial Agent-based Models
of Human-Environment Interactions
4:30–7:10pm, Robinson B218
Dr. Andrew Crooks
Department of Computational
Krasnow Institute for
Office hours: Room 381,
Research Hall, Friday 2:00-3:00, 4:30-5:00 or by appointment.
Class Web Site: https://sites.google.com/site/css645spring15/
This course will introduce
graduate students in the spatial, environmental, and computational social
sciences to the use of agent-based techniques as a means of modeling
human-environmental interactions. Emphasis will be placed on spatial processes,
the use of spatial identifiers to link socioeconomic and biophysical models,
and where possible, links to geographic information and associated
technologies. We will cover applications in areas such as agriculture, diseases,
forestry, biodiversity, habitat degradation, interactions between human
populations and nonhuman species and urban modeling.
The course will combine literature
review with some hands-on modeling. When demo versions are available, we will
compile and run models as we review articles based on those models. In
addition, students will complete a class project where they develop their own
models in their areas of interest. Students with no programming background can
develop simple models using NetLogo. Students with advanced programming
abilities will be encouraged to develop more sophisticated models using
packages such as Repast, SWARM, MASON. etc., or may develop their own spatial agent-based
model using the language of their choice.
Course Themes: Since the application of
agent-based modeling (ABM) to research on human-environment interactions is
still undergoing changes, standard methodology is still in development stages.
Therefore, we will focus our discussion on progress to date, and need for
further methodological development, in several key areas, including:
- Model ontologies and
theoretical models of decision making
- Empirical methods for
building agent decision models
- Modeling market
- Modeling institutions
- Modeling cross-scale feedbacks and interactions
- Integration of agent-based modeling and GIS
Understanding the behavior of complex models
- Model verification and validation.
Prerequisites: Students should have a
familiarity with spatial structures and concepts, some background in a social
science, and a high level of computing competence. Students should have some
familiarity with agent-based modeling and complexity theory, such as would be
provided by Introduction to Computational Social Science (CSS 600) or Land-Use
Modeling Techniques and Applications (CSS 643). Knowledge of a programming
language is helpful but not required. Additional readings will be suggested for
students lacking background in any of these areas. Generally, no one student
has background in all of these areas. Students are encouraged to make stronger
contributions in their areas of expertise, and to learn from the expertise of
others in their weaker areas.
Readings: Each week students will be
required to read 2-4 readings. Some weeks you have a choice—read carefully.
Short writing assignments (SWA) (30% of
grade): Most weeks there will be at least one short writing assignment.
Topics will be posted on the class website for that week. Starting the 11th
of February, each student will be required to complete a brief written
review of one of the weekly readings, based on the SWA questions on the class
SWA will be due by 9 AM on the Tuesday before class. Email me (firstname.lastname@example.org) the short writing
assignment and I will post them on the class website under the appropriate week
(students are expected to review each others SWA before the class meeting
time). Late short writing assignments
will not be accepted.
Presentations (25% of
grade): Students will each be required to give an in-depth review of 2
articles over the course of the semester, starting the 11th of February.
Presentation guidelines will be posted on the course website (https://sites.google.com/site/css645spring15/paper-presentation-guidelines).
Please note presentations are due to me
at 9am of the day of the class. Note
this and in class participation make up to 25% of your of your grade. If you
don’t understand the paper you may have to read around the subject. Additional
references on the class site should help here.
Term project and presentations (45% of
grade): Each student will complete a term modeling project in their area of
interest and will present the results to the class (students are encouraged to
work in groups of two if this option is chosen one grade per group will be
given). A minimum of 1000 (max 1500) word abstract/proposal of your project is due
on the 3rd of February. Please also include (separate to this length
requirement) any relevant citations (5-10 citations, probably no more than
that). The abstract should tell me:
- What is the research question
that you wish to investigate (as someone else puts it, what is the model
“for”; not what is the model “of”)?
- Why is this question
interesting and relevant?
- How will you address the
question? (What sort of model, what language, etc.)
final paper should be a minimum of 6000 words and no more than 8000 words
- Papers under or over these
limits will lose one quarter of a letter grade per 500 words.
- The paper is expected to be
of similar style to that of a journal article (as those reviewed in class
including the appropriate referencing style).
- Must utilize and be relevant
to material discussed in the class (i.e. must be a spatial agent-based
- Clearly describe the model
and discuss results.
- In addition to the paper, the
model code (in electronic format along with auxiliary material) is also
expected so I can run the model when grading the paper.
are expected to give a 20-minute presentation of their models along with their
findings to class at the end of the semester (in a similar style to that of a
final paper (including model code and data) is due Monday May 11th
at 9 AM (email them to email@example.com).
You may also create a web page with animations, model demo, etc. if you
like. Late papers will lose one quarter
of a letter grade per 24 hours.
short writing assignments will not be accepted. You may make up to two SWAs by
doubling up for another week, posting a writing on a seminar or conference
paper presentation that you attend, or completing another assignment that we
both agree on. If you are not able to present a paper of your choice on the
assigned day due to an authentic emergency, you will be asked to present
another paper later in the semester instead. (“I had to stay late at work” is
not an authentic emergency.) Other late work will lose one quarter of a letter
grade per day.
Student’s grades will be based on the following:
- 25%: Article
- 30%: Short writing
assignments, and class participation.
- 45%: Term project (10% for
initial abstract, 10% for final presentation, 80% for final paper).
policy: following the university policies, an “Incomplete” grade (IN) may
be assigned to a student who is passing a course but who may be unable to complete
scheduled course work due to a cause beyond reasonable control. Any
requests for an incomplete grade must be submitted in writing during the last week of classes, and should indicate the
reason for the request. If an IN grade is granted, it is your responsibility
to contact the instructor at the end of the semester to make proper
arrangements for completing any missing work. For further details on the IN
grade please visit: https://registrar.gmu.edu/topics/incomplete/
Please check before class to
ensure that cell phones are turned off.
integrity of the University community is affected by the individual choices
made by each of us. GMU has an Honor Code with clear guidelines regarding
academic integrity. Three fundamental and rather simple principles to follow at
all times are that: (1) all work submitted be your own; (2) when using the work
or ideas of others, including fellow students, give full credit through
accurate citations; and (3) if you are uncertain about the ground rules on a
particular assignment, ask for clarification. No grade is important enough to
justify academic misconduct.
means using the exact words, opinions, or factual information from another
person without giving the person credit. Writers give credit through accepted
documentation styles, such as parenthetical citation, footnotes, or endnotes.
Paraphrased material must also be cited, using MLA or APA format. A simple
listing of books or articles is not sufficient. Plagiarism is the equivalent of
intellectual robbery and cannot be tolerated in the academic setting. If you
have any doubts about what constitutes plagiarism, please see me.
in many classes, a number of projects in this class are designed to be
completed within your study group. With collaborative work, names of all the
participants should appear on the work. Collaborative projects may be divided
up so that individual group members complete portions of the whole, provided
that group members take sufficient steps to ensure that the pieces conceptually
fit together in the end product.
projects are designed to be undertaken independently. In the latter case, you
may discuss your ideas with others and conference with peers on drafts of the
work; however, it is not appropriate to give your paper to someone else to
revise. You are responsible for making certain that there is no question that
the work you hand in is your own. If only your name appears on an assignment,
your professor has the right to expect that you have done the work yourself,
fully and independently.
re-use of computer models is not acceptable. If one does use code from another
model, please ensure the code that is used is accredited to the original model
(just as you would do to a reference in a paper). Moreover, the re-use of papers,
presentations, etc., from one course in another course is not appropriate. I
expect that work that is submitted for this class has been done only for this
you have a documented learning disability or other condition that may affect
academic performance you should: 1) make sure this documentation is on file
with the Office of Disability Services (SUB I, Rm. 222; 993-2474; http://www.gmu.edu/student/drc/) to
determine the accommodations you need; and 2) talk with me to discuss your
The class website (https://sites.google.com/site/css645spring15/)
contains all the supplementary material needed for the course. Material for
each class including models is given in the assigned week.
Please note that course handouts (lecture slides) will not
be available until the day of the class, however core reading material and
references will be provided beforehand. I do not expect you to read all the
additional references; I provide them purely for a reference resource for
topics covered in class.
You should check this
website regularly for updates.
All readings are assigned as preparatory material to the
weekly meeting. The reading material for this course consists mostly of
required readings and optional recommended readings listed below and detailed
for each meeting. The optional readings may or may not be discussed in class,
depending on the time available, but is nonetheless included in the interest of
depth and completeness.
There is no defined textbook for this class. Articles and
chapters are available online or are made available on the course website.
Provisional Weekly Schedule of Topics
Along with Compulsory and Suggested Readings
Please note that the topics and
their order are subjected to change at the discretion of the instructor, any
changes will be announced in class.
F. and Le Page, C. (2004), 'Multi-Agent Simulations and Ecosystem Management:
A Review', Ecological Modelling,
176(3-4): 313-332. (Recommended).
A.T. and Heppenstall, A.J. (2012), Introduction to Agent-based Modelling, in
Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. (eds.), Agent-based Models of Geographical Systems,
Springer, New York, NY, pp. 85-108. (Recommended).
V. (2008), 'Ecological Models: Individual-Based Models', in Jorgensen, S.E.
and Fath, B.D. (eds.), Encyclopedia of
Ecology, pp. 1959-1968. (Required).
M.A. and Ostrom, E. (2006), 'Governing Social-Ecological Systems', in
Tesfatsion, L. and Judd, K.L. (eds.), Handbook
of Computational Economics: Agent-Based Computational Economics,
North-Holland Publishing, Amsterdam, Netherlands, pp. 1465-1509. (Recommended).
D.C., Manson, S.M., Janssen, M.A., Hoffmann, M.J. and Deadman, P. (2003),
'Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A
Review', Annals of the Association of
American Geographers, 93(2): 314-337. (Required).
None, get started on the readings.
Continued: Complexity in Human Environment Systems, Pattern Oriented Validation,
NetLogo Models & Resources
V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W.M., Railsback, S.F.,
Thulke, H., Weiner, J., Wiegand, T. and DeAngelis, D.L. (2005),
'Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from
Ecology', Science, 310: 987-991. (Required).
S.M., Sun, S. and Bonsal, D. (2012), Agent-Based Modeling and Complexity, in
Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. (eds.), Agent-based
Models of Geographical Systems, Springer, New York, NY, pp.
D.C., Berger, T. and Manson, S.M. (2001), Proceedings
of an International Workshop on Agent-Based Models of Land-Use and Land-Cover
Change. Irvine, CA, Available at http://www.csiss.org/maslucc/ABM-LUCC.htm. (Required).
D.C., Hessl, A. and Davis, S.C. (2008), 'Complexity, Land-use Modeling, and
the Human Dimension: Fundamental Challenges for Mapping Unknown Outcome
Spaces', Geoforum, 39(2): 789-804.
of 4 article presentation choices due on Jan. 27th, 9 am.
ABM/GIS Integration. Model Communication /Ontologies. Strategies for Parameterizing
Agent Decision Models.
M., Hamill, L. and Gilbert, N. (2011), Designing and Building an Agent-Based
Model, in Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. (eds.), Agent-based Models of Geographical Systems,
Springer, New York, NY, pp. 141-166. (Recommended).
A.T. and Castle, C. (2012), The Integration of Agent-Based Modelling and
Geographical Information for Geospatial Simulation, in Heppenstall, A.J.,
Crooks, A.T., See, L.M. and Batty, M. (eds.), Agent-based Models of
Geographical Systems, Springer, New York, NY, pp. 219-252. (Required).
A.T., Castle, C.J.E. and Batty, M. (2008), 'Key Challenges in Agent-Based
Modelling for Geo-spatial Simulation', Computers,
Environment and Urban Systems, 32(6): 417-430. (Required).
H.R. (2002), 'Integrating Geographic Information Systems and Agent-Based
Technologies for Modeling and Simulating Social and Ecological Phenomena', in
Gimblett, H.R. (ed.) Integrating
Geographic Information Systems and Agent-Based Modelling Techniques for
Simulating Social and Ecological Processes, Oxford University Press,
Oxford, UK, pp. 1-20. (Recommended).
D.C. (2005), 'Integration of Geographic Information Systems and Agent-Based
Models of Land Use: Challenges and Prospects', in Maguire, D.J., Batty, M.
and Goodchild, M.F. (eds.), GIS,
Spatial Analysis and Modelling, ESRI Press, Redlands, CA, pp. 403-422.
D.C., Brown, D., Polhill, G.J., Deadman, P.J. and Manson, S.M. (2008),
'Illustrating a New 'Conceptual Design Pattern' for Agent-Based Models of
Land Use via Five Case Studies - The MR POTATOHEAD Framework', in Paredes,
A.L. and Iglesias, C.H. (eds.), Agent-Based
Modelleling in Natural Resource Management, INSISOC, Valladolid, Spain,
pp. 29-62. (Recommended).
J.G., Parker, D., Brown, D. and Grimm, V. (2008), 'Using the ODD Protocol for
Describing Three Agent-Based Social Simulation Models of Land-use Change.' Journal of Artificial Societies and Social
Simulation, 11(2): 3, Available at http://jasss.soc.surrey.ac.uk/11/2/3.html. (Recommended).
D.T., Brown, D., Parker, D.C., Schreinemachers, P., Janssen, M.A., Huigen,
M., Wittmer, H., Gotts, N., Promburom, P., Irwin, E., Berger, T., Gatzweiler,
F. and Barnaud, C. (2007), 'Comparison of Empirical Methods for Building
Agent-based Models in Land Use Science', Journal
of Land Use Science, 2(1): 31–55. (Recommended).
Term paper topic and short
abstract (1000 words) due on the 3rd of Feb. at 9am
Robinson, D.T., Moran, E. and Brondizio, E. (2004), 'Effects of Colonist
Household Structure on Land Use Change in the Amazon Rainforest: An Agent
Based Simulation Approach', Environment
and Planning B, 31(5): 693-709.
T.A., Kresl, J., Van Wes, Q., Carr, E. and Wilshusen, R.H. (2000), 'Be There
Then: A Modeling Approach to Settlement Determinants and Spatial Efficiency
Among Late Ancestral Pueblo Populations of the Mesa Verde Region, U.S.
Southwest', in Kohler, T.A. and Gumerman, G.J. (eds.), Dynamics in Human and Primate Societies: Agent-Based Modeling of
Social and Spatial Processes, Oxford University Press, Oxford, UK, pp.
T. A., See, L. M., & Drake, F. (2009). An agent-based approach to
simulating the dynamics of shifting cultivation in an upland village in
Vietnam. European Journal of GIS and Spatial Analysis, 19 (4), 493–522.
D.C., Entwisle, B., Rindfuss, R., Vanwey, L., Manson, S.M., Moran, E., An,
L., Deadman, P.J., Evans, T., Linderman, M., Mussavi Rizi, M.S. and Malanson,
G. (2008), 'Case Studies, Cross-site Comparisons, and the Challenge of
Generalization: Comparing Agent-based Models of Land-use Change in Frontier
Regions', Journal of Land Use Science,
3(1): 41-72. (Required).
K., Kellermann, K. and Balmann, A. (2006), 'Agent-based Analysis of
Agricultural Policies: An illustration of the Agricultural Policy Simulator
AgriPoliS, Its Adaptation, and Behavior', Ecology and Society, 11(1): 49,
Available at http://www.ecologyandsociety.org/vol11/iss1/art49/.
Read Parker et al., and 1 of 4
others. Standard SWA on one article.
Slums and Urban Poverty
D., Lees, M. H., Palavalli, B., Pfeffer, K., & Sloot, M. P. (2014). The Emergence
of Slums: A Contemporary view on Simulation Models. Environmental Modelling
& Software, 59, 76-90. (Required).
E., Flacke, J. and Retsios, B. (2011), 'Simulating Informal Settlement Growth
in Dar es Salaam, Tanzania: An Agent-based Housing Model', Computers, Environment and Urban Systems,
J. (2012), Exploring Urban Dynamics in Latin American Cities Using an
Agent-Based Simulation Approach, in Heppenstall, A.J., Crooks, A.T., See,
L.M. and Batty, M. (eds.), Agent-based
Models of Geographical Systems, Springer, New York, NY, pp. 571-590.
A., Crooks, A.T. and Koizumi, N. (2012), Slumulation: an Agent-based Modeling
Approach to Slum Formations, Journal of
Artificial Societies and Social Simulation, 15 (4). Available at http://jasss.soc.surrey.ac.uk/15/4/2.html
Roy et al., and 1 of 3 others.
Standard SWA on one article.
Urban Models: Overview and Gentrification
I. and Torrens, P.M. (2004), 'Modeling Urban Dynamics with Multiagent
Systems', in Benenson, I. and Torrens, P.M. (eds.), Geosimulation: Automata-Based Modelling of Urban Phenomena, John
Wiley & Sons, London, UK, pp. 153-248. (Required).
L. and Bolchi, P. (2008), 'Smith’s Rent gap Theory and Local Real Estate
Dynamics: A Multi-agent Model', Computers, Environment and Urban Systems, 32(1): 6 - 18.
J., Forest, B. and Sengupta, R. (2008), 'Agent-Based Simulation of Urban
Residential Dynamics and Land Rent Change in a Gentrifying Area of Boston', Transactions in GIS, 12(4): 475-491.
D. (2002), 'Toward Micro-scale Spatial Modeling of Gentrification', Journal of Geographical Systems, 4(3):
P.M. and Nara, A. (2007), 'Modelling Gentrification Dynamics: A Hybrid
Approach', Computers, Environment and Urban Systems, 31(3): 337-361.
Read Benenson and Torrens (not for SWA) and one other. SWA on any of
Models: Residential Land Markets
Filatova, T., Parker, D. and van der Veen, A. (2009),
'Agent-Based Urban Land Markets: Agent's Pricing Behavior, Land Prices and
Urban Land Use Change', Journal of
Artificial Societies and Social Simulation, 12(1), Available at http://jasss.soc.surrey.ac.uk/12/1/3.html.
N.R., Safirova, E., McConnell, V., and Walls, M. (2011). An economic
agent-based model of coupled housing and land markets (CHALMS). Computers,
Environment, and Urban Systems, 35(3): 183-191
D.C. and Filatova, T. (2008), 'A Conceptual Design for a Bilateral
Agent-Based Land Market with Heterogeneous Economic Agents ', Computers, Environment and Urban Systems,
S. and Crooks, A.T. (2012), Agent Based Modelling and GIS for Community
Resource Management: Acequia-based Agriculture, Computers, Environment and
Urban Systems, 36(6): 562-572.
P.M. (2007), A Geographic Automata Model of Residential Mobility, Environment
and Planning B, 34(2): 200–222
Read Parker and Filatova and
one of the two others.
SWA on any.
V. and Railsback, S.F. (2005), 'Introduction', in Grimm, V. and Railsback,
S.F. (eds.), Individual-Based Modeling
and Ecology, Princeton University Press, Princeton, NJ, pp. 3-21. (Required, not for student presentation).
P. and Hesper, B. (1983), 'The Ontogeny of the Interaction Structure in
Bumble Bee Colonies: A MIRROR Model', Behavioral
Ecology and Sociobiology, 12(4): 271-283.
W.M., Bennetts, R.E., Kitchens, W.M. and DeAngelis, D.L. (2002), 'Exploring
the Effect of Drought Extent and Interval on the Florida Snail Kite:
Interplay Between Spatial and Temporal Scales', Ecological Modelling, 149(1-2): 25-39
S.F. and Harvey, B.C. (2002), 'Analysis of Habitat Selection Rules using an
Individual-based Model', Ecology,
Read Grimm and Railsback plus
at least 1 other; SWA on Hogeweg or Mooij or Railsback
M. (2003), Agent-Based Pedestrian Modelling, Centre for Advanced Spatial Analysis (University College London):
Working Paper 61, London, UK. (Required,
not for student presentation).
M., Desyllas, J. and Duxbury, E. (2003), 'Safety in Numbers? Modelling Crowds
and Designing Control for the Notting Hill Carnival', Urban Studies, 40(8):
H.R., Richards, M.T. and Itami, R.M. (2002), 'Simulating Wildland Recreation
Use and Conflicting Spatial Interactions using Rule-Driven Intelligent
Agents', in Gimblett, H.R. (ed.) Integrating
Geographic Information Systems and Agent-Based Modelling Techniques for
Simulating Social and Ecological Processes, Oxford University Press,
Oxford, UK, pp. 211-243.
D.A. and Tang, W. (2006), 'Modelling Adaptive, Spatially Aware, and Mobile
Agents: Elk Migration in Yellowstone', International Journal of Geographical
Information Science, 20(9): 1039-1066.
Read Batty (2003) Ped Mod plus
at least 1 other. SWA on 1 other.
Disasters and Disease
G. I., Coates, G., Wilson, D. T., & Crouch, R. S. (2012). Agent-based
simulation for large-scale emergency response: A survey of usage and
implementation. ACM Computing Surveys (CSUR), 45(1), 8. (Required)
A.T. and Wise, S. (2013), GIS and Agent-Based models for Humanitarian
Assistance, Computers, Environment and Urban Systems, 41: 100-111.
A.T. and Hailegiorgis, A.B. (2014), An Agent-based Modeling Approach Applied
to the Spread of Cholera, Environmental Modelling and Software, 62: 164-177.
J.M., Pankajakshan R., Hammond, R.A. (2011) Combining Computational Fluid
Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning.
PLoS ONE 6(5): e20139. doi:10.1371/journal.pone.0020139.
J. (2012), 'An Agent-Based/Network Approach to Spatial Epidemics', in
Heppenstall, A.J., Crooks, A.T., See, L.M. and Batty, M. (eds.), Agent-based
Models of Geographical Systems, Springer, New York, NY, pp. 591-610.
Read Howe et al., SWA on 1
L., Linderman, M., Qi, J., Shortridge, A. and Liu, J. (2005), 'Exploring
Complexity in a Human– Environment System: An Agent-Based Spatial Model for
Multidisciplinary and Multiscale Integration', Annals of the Association of American Geographers, 95(1): 54-79.
S.J., Westervelt, J.D. and Trame, A. (2002), 'Management Application of an
Agent-Based Model: Control of Cowbirds at the Landscape Scale', in Gimblett,
H.R. (ed.) Integrating Geographic
Information Systems and Agent-Based Modelling Techniques for Simulating
Social and Ecological Processes, Oxford University Press, Oxford, UK, pp.
R., Bousquet, F., Le Page, C. and Antona, M. (2003), 'Agent-Based Simulations
of Interactions Between Duck Population, Farming Decisions and Leasing of
Hunting Rights in the Camargue (Southern France)', Ecological Modelling, 165(2-3): 107-126.
Read 2 of 3. SWA on any one of
ABM applied to human-environment interactions
F., Barreteau, F.O., d'Aquino, P., Etienne, M., Boissau, S., Auber, S., Page,
C.L., Babin, D. and Castella, J.C. (2003), 'Multi-agent Systems and Role
Games: An Approach for Ecosystem Management', in Janssen, M.A. (ed.)
Multi-Agent Approaches for Ecosystem Management, Edward Elgar, Cheltenham,
UK., pp. 248-285. (Required)
M., Immers, L.H., Waaldijk, F.A. and Stoelhorst, H.J. (2003), 'Gaming
Approach Route 26: A Combination of Computer Simulation, Design Tools and
Social Interaction', Journal of Artificial Societies and Social Simulation,
6(3), Available at http://jasss.soc.surrey.ac.uk/6/3/7.html.
M., Le Page, C. and Cohen, M. (2003), 'A Step-by-step Approach to Building
Land Management Scenarios Based on Multiple Viewpoints on Multi-agent System
Simulations', Journal of Artificial Societies and Social Simulation, 6(2),
Available at http://jasss.soc.surrey.ac.uk/6/2/2.html.
Read Bousquet et al., SWA on any
of the other 2
Class, Dr. Crooks is out of town, work on your projects
Student Project Presentations
The final paper (including model code and data) is due Monday
May 11th at 9 AM (email them to firstname.lastname@example.org).
Note: Recording of any kind (audio,
video), reuse of course materials, and further dissemination of the course
content is not permitted unless prior written consent of the professor and
George Mason University has been given or if recording is part of an approved