Agent-Based Modeling and Simulation (ABMS) Bertan Badur badur@boun.tr Department of

1. Agent-Based Modeling and Simulation (ABMS) Bertan Badur badur@boun.edu.tr Department of Management Information Systems Boğaziçi University

2. Outline Introduction Searching Mushrooms in a Forest

3. Introduction • NetLogo • simple to install and experiment its model library • User Manual • Tutorials, Interface Guide and Programming Guide • Dictionary • Model Library • code examples

4. Agents • Four kind of agents • Moving agents – Turtles • Patches – square cells – space in world • Links – connect two turtles networks • Observer - controler of the model • create other agents • global variables • Each type of agents • commands • variables – • build-in such as color and location • user defined – additional • observer – gloabal variables

5. Global variables: • all agent can read and change • environment characteristics • model parameters • Primitives – build-in procedure or command • commands • tell agents something to do – retukrn void • reoprters • calculte and report something – return a value or list • Ex: mean reports mean of a list of numbers • neighbors reports list of surrounding patches

6. Context • each pice of code is “in the contxt of ” one kind or occationally more then one kind of agent • can be changed during execution • Ex: ask turtles [move] • agents – directly access variables for their own type • Exceptions: • observer varibles by all agents • turtles can access patchs variables they are currenlty on

7. Searching Mushrooms in a Forest • Is there a best strategy for searching mushrooms? • observation: • mushrooms in clusters • An intuitive strategy: • scanning an area in wide sweeps • upon finding a mushroom turning to smaller scale sweeps • as mushrroms in clusters • What is large, small sweeps? and • How long to search in smaller sweeps? • Humans searching • pizzas, jobs, low prise goods, peace with neighbors

8. model of the problem • try different search strategies • Purpose: • what search strategy maximizes musrooms found in a given time • Ignore trees and vegitables, soil type • Musrooms are distributed as clusters • mushroom hunter • moving point • having a sensing radius • track of how many mushrooms found • how much time passed since last mushroom fouınd

9. clusters of items (mushrooms) • If the agent (hunter) finds an item • smaller-scale movement • If a critical time passes since last item found • swithes back to more streight movement • so as to find new clusters of items

10. Demonstrating Program: Mushroom Hunt • File/New • File/Save with extension “nlogo” • Settings • World geometry: • 0,0 orgin, max-pxcor=16, max-pycor=16 • 33x33 squre latice • 2 hunters – turtels • cluster of mushrooms – red patches • all other patches are black • setup – initialization • go – continuous operations

11. procedukres – commands • to proc 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

12. to setup end to go end

13. to setup ask patches [ set pcolor red ] 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

14. to setup ask n-of 4 patches [ ask patches in-radius 5 [ set pcolor red ] ] end n-of: n-of number ageent set in-radius : agents in-radius number

15. to setup ask n-of 4 patches [ ask n-of 20 patches in-radius 5 [ set pcolor red ] ] end 4 patches are randomly selected for each randomly selected pathc for all patches in radius 5 select 20 randomly set their color to red

16. to setup clear-all ;abriviares as – ca - ask n-of 4 patches [ ask n-of 20 patches in-radius 5 [ set pcolor red ] ] end clear-all: clear all default values

17. using parameters globals [ num-clusters ] to setup clear-all set num-clusters 4 ask n-of num-clusters patches [ ask n-of 20 patches in-radius 5 [ set pcolor red ] ] end

18. creating 2 hunters - turtles create-tutrles 2 ;crt 2 [ set sıze 2 set color yellow ] create 2 turtles crt create-tutles bnild-in turtle variables size and color

19. go procedure to go ask turtles [search] end to search ifelse tıme-sınce-last-found <= 20 [right (random 181) - 90] [right (random 21) - 10] forward 1 end cifelse boolean condition [ block whan true ] [ block when false ] right: turn right by angle in degrees

20. algorithm of move if timelast-found <= critical value make a small turn else make a biger turn if found – come on a red patch set timelasf-fournd to 0 set color to yellow else increment timelast-found by one

21. variable for turtles tutrles-own [ tıme-sınce-last-found ] tıme-sınce-last-found variable for all turtles time passed since last mushroom has found by the hunter

22. tıme-sınce-last-found initial value crt 2 [ set sıze 2 set color yellow set tıme-sınce-last-found 999 ] initialze tıme-sınce-last-found to a very high value greater then 20

23. add to the search procedure ifelse pcolor = red [ set tıme-sınce-last-found 0 set pcolor yellow ] [ set tıme-sınce-last-found tıme-sınce-last-found + 1 ] end if found pcolor is red set tıme-sınce-last-found to 0 set pcolor yellow else increment tıme-sınce-last-found by one

24. command center • select turtles • write commands • hatch 1 [right 160] • show count turtles

25. firther modifications • adding ticks • add reset-ticks • to the end of setup • add tick to the begining of go • following motion of hunters • add pen-down to the setup procedute when initilizing turtles