COLQ 201, Multiagent Modeling

Time and place: MWF 3:30 - 4:30
Prof. Harry Howard
howard at tulane dot edu
Office: Newcomb Hall 322-D
862-3417 (voice mail 24 hours a day)
Office hours: ???

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:

Schedule of assignments, Spring 2010
NetLogo User Manual [NLUM]
The links in the Assignment column are to the simulations that we will discuss in class that day.
Many simulations will have background readings assigned from other sources which I will make available on MyTulane in due course.

Date

Day

Topic

Assignment

ppt
mp3

Q/P

Jan 11 (M)

1

Introduction to the course

 

13 (W)

 2

Introduction to NetLogo

NLUM: What is NetLogo? Sample Model: Party

 

15 (F)

3

Models in NetLogo

NLUM: Tutorial #1: Models - Wolf Sheep Predation

 

18 (M)

 

MLK Birthday

 

20 (W)

4

Earth sciences: diffusion

NetLogoGreenHouse, Climate change,

 

22 (F)

5

Biology: flocking, herding & schooling

Boids, MyFlocking

25 (M)
6

Biology: from foraging to graph theory

Ants2, AntSystem,

   
Q1

27 (W)

7
Biology: migration
Scatter, Randomly walking,
 

29 (F)

8
AI: navigation
Path finder,
 

Feb 1 (M)

9

Urbanism: traffic

Traffic basic, Traffic grid, Traffic simulation,

Q2

3 (W)

10

Biology: individual vs. collective movement

Independence vs. mimetism,

 

5 (F)

11
Biology: communication
Quorum sensing,
 

8 (M)

12

Epidemiology: spread of disease

Malaria control, Multiple-drug resistant tuberculosis, AIDS

Q3

10 (W)

13

Epidemiology: the SIR model

Disease in groups, Epidemic typhoid fever on disaster area,

 

12 (F)

14
Epidemiology: night of the living dead
Zombie infection, Zombie infection 2, yet another Zombie infection 2
 

15 (M)

 

Lundi Gras

     

17 (W)

15

Ecology: predator-prey models

Wolf-sheep predation, Wolf-sheep predation refuge, Pollution,

   

19 (F)

16

Ecology: predator-prey evolution

Bug hunt evolution, Community structure v4,

     

22 (M)

17

Biology: population genetics

PopGen fishbowl 1,

   
Q4

24 (W)

18

Evolutionary biology: game theory 1

Evolutionary game theory Mayberry ESS,

     

26 (F)

19

Evolutionary biology: game theory 2

Evolutionary game theory big bird replicator dynamic

     

Mar 1 (M)

20

Evolutionary biology: social factors

Altruism, Cooperation, Divide the cake.

   

Q5

3 (W)

21

Anthropology: agrarian societies

Southern African Agrarian Humans Suite,

     

5 (F)

22

Anthropology: aggression & ethnocentrism

Homo bellicus, Ethnocentrism.

     

8 (M)

23
Anthropology: cultural dissemination
Axelrodv2,    

Q6

10 (W)

24

Urbanism: why live in cities?

Urbanization MC, Urban transition, Positive feedback,

     

12 (F)

25
Urbanism: clustering 1
Structure from randomness 1 and 2,      

15 (M)

26

Urbanism: clustering 2

Cluster, Segregation, Path dependence, Sprawl effect,

   

Q7

17 (W)

27

Urbanism: misc

Shopsim, Awareness,

     

19 (F)

28
Urbanism: real example
TijuanaBordertowns,      

22 (M)

29
Economics: distribution of wealth
Wealth distribution, Economic disparity,    

Q8

24 (W)

30
Economics: rational agent model
El Farol, Minority game,      

26 (F)

31
Economics: banking
BankReserves, Cash flow,      

29 (M)

Spring Break

   

31 (W)

Spring Break

     

Apr 2 (F)

Spring Break

     

5 (M)

32
Economics: customers & consumers
customerBehavior, consumerism project,    

7 (W)

33

Decision making: prisoner's dilemma

LogoMoth,

     

9 (F)

34

Decision making: negotiation

Negotiations,

     

12 (M)

35

Organizational psychology

March, Miller,

 
Q9

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

21 (W)

39

Communications: spread of rumors & innovation

Rumor, Innovation

   

23 (F)

40
Linguistics
Language change,      

26 (M)

41
Last quiz, party
   
Q11

May ? (?)

42

FINAL EXAM DAY

     

Go back to Harry Howard's home page

Inception: 26-Sept-09. Last revision: October 29, 2009 . HH