1. Creating Simple Agent-Based Models
MIS 643
Agent-Based Modeling
amd Simulation
2016/2017 Fall
Creating Simple Agent-Based Models

2. Outline
Intorduction
Life
Heroes and Cowards
Simple Economy

3. Introduction Intorduction to Agent-Based Modeling
by U. Wilensky and W. Rand
Chapter 2

4. Introduction learn to construct simple ABMs
“toy models” – not mean models of real phenomena
thought experiments
objects to think with
simple to construct but
exebits interesting, suprising emergent behavior

5. Outline
Intorduction
Life
Heroes and Cowards
Simple Economy

6. Life In 1970 British mathematician John Horton Conway, Conway (1976)
cellular automata - the “Game of Life”
Martin Gardner,
Scientific American colomn

7. The Game Played on checkeboard – graph paper N x N cells – can be
“alive” or “dead”: state of a cell
surrounded by
eight neighbour cells
the grid is “wrap around”
clock ticks – generation

8. Rules of the Game
Each cell checks its own state and states of its neighbors and
set itself as “alive” or ”dead”
if the cell has less than 2 alve neighbors
it dies
if it has more than 3 alive neighbors
it also dies
if it has 2 alive neighbors
it remains in its current state
if it has 3 alive neighors
if dead become alive, if alive, stay alive

9. NetLogo NetLogo has three tabs Interface tab Code tab Info tab
black area – “view”
white area – interface
set user interface elements; buttoms, siliders..
observe results: output, plots....
Code tab
Info tab

10. The view composed of grid of cells – patches how to open
click settings in toolbar or
on the visw double click and select edit
Parameters to set
Location of orgin
max-pxcor, max-pycor 25
patch size: 13 to 8
world wraps hirizonally, vertically, see IABM-WR pp 55 Box 2.1 Wrapping

11. NetLogo Code modules – procedures begin with to end with end usually
setup
initializations go
processes taking place advences clock by tick

12. Procedures procedures – commands to procedure_name commands end
Create a button executing procedure setup
Create a button executing procedure go
forever is cheked – forever button
write setup procedure
code tab

13. Procedures (cont.)
to setup
end
to go

14. Initialization to setup ;; ask patches [ comands ]
.. ;; other commnads
end
ask primitive asks selected agents to do actions by commands in brackets
set color of all pathces to red
set - primitive is assignment
pcolor – variable for patches

15. Initialization - algorithm
to setup
;; clear all setings
;; set dead patches to blue
;; 10% of patches are alive
;; initilize clock
end

16. to setup
clear-all
ask patches [
set pcolor blue
if random 100 < 10
[ set pcolor green ] ]
reset-ticks
end

17. Exercise
What is the difference between asking exactly 10% of the patches being alive
How do you perform this in general for any number of patches, exactly X% being alive
the chance of a randomly seleced patch being alive is 10%

18. Box 2.2: Agent Centreric Thinking
WR-IABM Chapter 2
Box 2.2

19. Asking Patches Probabilistically
each patch performs the tasks in ask with a probability
probability of a patch being green is 0.1
in each run different number of patches turn into green

20. Probability of a Patch being green
ask patches [
if random 100 < 10
[set pcolor green] ;; end if
] ;; end ask or
ask patches with [random 100 < 10]
[ set pcolor green ]

21. Asking exactly 10% of patches
to setup
ask no-of
0.1*(51*51) patches
[ set pcolor green ]
] ;; end ask
] ;;end setup
or more generally
let number-of-patches count patches
0.1*number-of-patches patches

22. go Procedure - algorithm
to go
;; each patch counts its alive neighbors
;; number of green neighboring patches
;; patches with 3 green naigbors turn or stay green
;; patches with 0 or 1 green neighbors turn or stay blue
;; patches with 4 or higher neighbors turn to blue
end

23. go Implementation to go ask patches [
set live-neighbors count neighbors with [pcolor = green] ]
if live-neighbors = 3 [set pcolor green]
if live-neighbors = 1 or live-neighbors = 0 [set pcolor blue]
if live-neighbors >= 4 [set pcolor blue]

24. clear-all to setup clear-all ;abriviares as – ca - ask patches [
set pcolor blue
if random 100 < 10
[ set pcolor green ] ]
end
clear-all: clear all default values

25. variable for patches patches-own [ live-neighbors ]
different variable for each patch
initialized to 0

26. firther modifications
adding ticks
add reset-ticks
to the end of setup
add tick to the begining or as a last statemet of go procedure

27. to setup
clear-all
ask patches [
set pcolor blue
if random 100 < 10
[ set pcolor green ] ]
reset-ticks
end

28. to go
ask patches [
set live-neighbors count neighbors with [pcolor = green] ]
if live-neighbors = 3 [set pcolor green]
if live-neighbors = 1 or live-neighbors = 0 [set pcolor blue]
if live-neighbors >= 4 [set pcolor blue]
] ;; end ask
tick
] ;; end go procedure

29. Stable Patterns
1 – Still Lifes: stable shapes unless other shapes collide with them
block, the beehive, the loaf,...
2 – Oscillators: repeat over time
3 – Spaceships: move across the life world
Unstable Patterns:
guns: a pattern with a main part thatg repeats like an oscillator and periodically emits spaceships

30. One dimensional CA with only one neighbor in each side
In 1983, Stephan Wolfram – physisist and mathematical software entrepreneur
One dimensional CA with only one neighbor in each side
classified all possible rules into four behavioral regions
homogenous, periodic, chatoic and complex
Complexity in nature – due to CA like simple mechanisms

31. Outline
Intorduction
Life
Heroes and Cowards
Simple Economy

32. Heroes and Cowards

33. Rules of the game with people each choose a heroe and an enemy
two stages:
first every one act – cowardly
move be sure that your friend is always between you and your enemy
hiding from your enemy behind your friend cowardly
second – behave like a heroe
move between your friend and enemy
protecting your friend from your enemy – herotic manner

34. setup pseudocode to setup ;; clear all previous settings variables
;; make patches white
;; create a set of turtles reand tne number froma slider
;; set x y corrdinates randomly
;; set colors to blue for cowards and red for heroes
;; if mixed is choosen determine crowads and heroes randomly while settng their colors
;; set one other turtle as their friends and oneother turtle as their enemies
;; reset ticks
end

35. setup code turtles-own [friend enemy] to setup ca
ask patches [set pcolor white]
crt number [
setxy random-xcor random-ycor
if personalities = "cowardly" [set color red]
if personalities = “breverly" [set color blue]
if personalities = "mixed" [set color one-of [blue red]]
set friend one-of other turtles
set enemy one-of other turtles ]
reset-ticks
end

36. Interface elements slider: Chooser Settings variable: number
default 68
Chooser
variable: personalities
choices: “coward”, “heroe”, ”mixed”
Settings
wrap off

37. go pseudocode go at each tick
if the agent is heroe act brawely – in a herotic manner
if the agent is cowars act cowardly
advance clock by one
end

38. to go
ask turtles [
if color = blue [act-bravely]
if color = red [act-cowadly] ]
tick
end

39. acting submodels to act-bravely
;; move toward the mod of your friend and your enemy
facexy ([xcor] of friend + [xcor] of enemy) / 2
([ycor] of friend + [ycor] of enemy) / 2
fd 0.1
end
to act-cowadly
;; set your friend between you and your enemy
facexy [xcor] of friend + ([xcor] of friend - [xcor] of enemy) / 2
[ycor] of friend + ([ycor] of friend - [ycor] of enemy) / 2

40. Random number generation
sequance of random numbers
initial value is taken from the clock of computer
if you want to strart from the same seed
random-seed 137
show random 100
always generate the same sequance of random numbers

41. Outline
Intorduction
Life
Heroes and Cowards
Simple Economy

42. Simple Economy Economies – heterogenous actors
buyers and sellers
in 1996, J. Epstein, R. Axtell,
SugerScape

43. Fixed number of people: 500
each starting out with inital amount of money: 100
At each tick,
each person gives one of her 1 dollar‘s to any other person at random
What will happen to the distribution of money?
constraint – total amount of money fixed
no one can have negative money
if income is zore, connot give any away

44. is there a limiting distribution of money? Intiution:
flat –
initially every body has the saime money
randomly seleced one to give
normal -

45. Version 1 to setup ;; clear everything
;; create 500 turtles with an initial wealth of 100 each
;; reset tick
end

46. setup turtles-own [wealth] to setup ca crt 500 [ set wealth 100 ]
reset-ticks
end

47. Version 1 to go ;;ask turles to transact if they have positive wealth
;; advence clock
end
to transact ;; contect turtle
;; decrement wealth of current turtle by one
;; for one of the other turtles, increment its wealth by one

48. go and transact to go ask turtles with [wealth > 0] [transact] tick
end
to transact
set wealth wealth - 1
ask one-of other turtles [set wealth wealth + 1]

49. Exercises can you move the wealth chacking condition to transact?
can you use with instead of if?

50. Monitoring by histogram
Adjust settings world size
orgine: left button
max-xcor 500
max-ycor 80
patch size 1
no wraping in both dimensions
Interface – plot
max-x:500, max-y:40
histrogram [wealth] of turtles
pen mode: bar

51. Using view with an histogram
For turtles:
size:2
color: green
shape: “circle”
x coordinate of view – wealth
y coordinate of view – randomly assigned kind of bar of a histogram

52. Version 2 setup turtles-own [wealth] to setup ca crt 500 [ set size 2
set shape "circle"
set color green
set wealth 100
setxy wealth random-ycor ]
reset-ticks
end

53. go and transact to go ask turtles with [wealth > 0] [transact]
ask turtles [ if wealth <= max-pxcor [set xcor wealth]]
tick
end
to transact
set wealth wealth - 1
ask one-of other turtles [set wealth wealth + 1]