Description: Multiagent Modeling teaches you that simple rules underlie complex phenomena. In particular, it demonstrates how a population of agents that interact with one another and with their environment according to simple instructions can simulate a variety of seemingly unrelated phenomena in the earth sciences, biology, urban studies, artificial intelligence, epidemiology, ecology, evolutionary biology, anthropology, economics, decision theory, organizational psychology, political science, communications, and linguistics. Rather than having you go out into the real world and perform costly and painstaking experiments on the atmosphere, forests, wolves and sheep, banks, farmers, superhighways, cities or villages, you will learn how to use a 2D modeling environment called NetLogo to populate an artificial world of your design with agents that do your bidding, or at least follow the rules that you impose on them. When you run your model world, its agents will interact over time, and you may see complex, and often unexpected, patterns develop among them.
As a by-product, you should be able to talk to almost anyone about almost anything. This can be useful in a job interview or a cocktail party. Don't think that Tulane doesn't teach you practical stuff.
Did I mention that this is going to be fun? Go ahead and try out the NetLogo simulation Mimicry <http://ccl.northwestern.edu/netlogo/models/Mimicry>. Read the text and then click the link "Run Mimicry in your browser". Move the slider at the top right more towards the right so that the simulation will run faster, click the setup button and then the go button. What happens to the viceroys? And more importantly, do you understand how it happens?
Objectives:
Outcomes: For you to demonstrate your attainment of these objectives, you will perform the following tasks:

Code of Academic Integrity
“The integrity of Newcomb-Tulane College is based on the absolute honesty of the entire community in all academic endeavors. As part of the Tulane University community, students have certain responsibilities regarding work that forms the basis for the evaluation of their academic achievement. Students are expected to be familiar with these responsibilities at all times. No member of the university community should tolerate any form of academic dishonesty, because the scholarly community of the university depends on the willingness of both instructors and students to uphold the Code of Academic Conduct. When a violation of the Code of Academic Conduct is observed it is the duty of every member of the academic community who has evidence of the violation to take action. Students should take steps to uphold the code by reporting any suspected offense to the instructor or the associate dean of the college. Students should under no circumstances tolerate any form of academic dishonesty.” For further information, point your browser at http://college.tulane.edu/honorcode.htm.
Violations of the Code of Academic Integrity will not be tolerated in this class. I will rigorously investigate and pursue any such transgression.
Students with disabilities who need academic accommodation should:
Date |
Day |
Topic |
Assignment |
ppt |
mp3 |
Q/P |
Jan 11 (M) |
1 |
Introduction to the course |
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13 (W) |
2 |
Introduction to NetLogo |
NLUM: What is NetLogo? Sample Model: Party |
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15 (F) |
3 |
Models in NetLogo |
NLUM: Tutorial #1: Models - Wolf Sheep Predation |
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18 (M) |
MLK Birthday |
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20 (W) |
4 |
Earth sciences: diffusion |
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22 (F) |
5 |
Biology: flocking, herding & schooling |
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25 (M) |
6 |
Biology: from foraging to graph theory |
Q1 |
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27 (W) |
7 |
Biology: migration |
Scatter, Randomly walking, | |||
29 (F) |
8 |
AI: navigation |
Path finder, | |||
Feb 1 (M) |
9 |
Urbanism: traffic |
Q2 |
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3 (W) |
10 |
Biology: individual vs. collective movement |
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5 (F) |
11 |
Biology: communication |
Quorum sensing, | |||
8 (M) |
12 |
Epidemiology: spread of disease |
Q3 |
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10 (W) |
13 |
Epidemiology: the SIR model |
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12 (F) |
14 |
Epidemiology: night of the living dead |
Zombie infection, Zombie infection 2, yet another Zombie infection 2 | |||
15 (M) |
Lundi Gras |
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17 (W) |
15 |
Ecology: predator-prey models |
Wolf-sheep predation, Wolf-sheep predation refuge, Pollution, |
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19 (F) |
16 |
Ecology: predator-prey evolution |
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22 (M) |
17 |
Biology: population genetics |
Q4 |
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24 (W) |
18 |
Evolutionary biology: game theory 1 |
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26 (F) |
19 |
Evolutionary biology: game theory 2 |
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Mar 1 (M) |
20 |
Evolutionary biology: social factors |
Q5 |
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3 (W) |
21 |
Anthropology: agrarian societies |
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5 (F) |
22 |
Anthropology: aggression & ethnocentrism |
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8 (M) |
23 |
Anthropology: cultural dissemination |
Axelrodv2, | Q6 |
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10 (W) |
24 |
Urbanism: why live in cities? |
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12 (F) |
25 |
Urbanism: clustering 1 |
Structure from randomness 1 and 2, | |||
15 (M) |
26 |
Urbanism: clustering 2 |
Q7 |
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17 (W) |
27 |
Urbanism: misc |
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19 (F) |
28 |
Urbanism: real example |
TijuanaBordertowns, | |||
22 (M) |
29 |
Economics: distribution of wealth |
Wealth distribution, Economic disparity, | Q8 |
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24 (W) |
30 |
Economics: rational agent model |
El Farol, Minority game, | |||
26 (F) |
31 |
Economics: banking |
BankReserves, Cash flow, | |||
29 (M) |
Spring Break |
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31 (W) |
Spring Break |
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Apr 2 (F) |
Spring Break |
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5 (M) |
32 |
Economics: customers & consumers |
customerBehavior, consumerism project, | |||
7 (W) |
33 |
Decision making: prisoner's dilemma |
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9 (F) |
34 |
Decision making: negotiation |
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12 (M) |
35 |
Organizational psychology |
Q9 |
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14 (W) |
36 |
Political science: civil violence,
colonialism |
Rebellion, Colonialism, | |||
16 (F) |
37 |
Political science: voting |
Voting, Voting - network knowledge, Voting - network vote choice | |||
19 (M) |
38 |
Political science: international environmentalism |
Cooperative countries, | Q10 |
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21 (W) |
39 |
Communications: spread of rumors & innovation |
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23 (F) |
40 |
Linguistics |
Language change, | |||
26 (M) |
41 |
Last quiz, party |
Q11 |
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May ? (?) |
42 |
FINAL EXAM DAY |