MIS 585 Special Topics in MIS AgentBased Modeling

MIS 585 Special Topics in MIS: Agent-Based Modeling 2015/2016 Fall

Outline Virtual Corridors of Butterflies From ODD to Net. Logo Implementation

Virtual Corridors of Butterflies • virtual corridores – Peer et al. (2005) • mate-finding by butterflies (bf) • “hilltopping” strategy - males and females – uphills for meet and mate • Simple model • formulation by ODD protocol

Purpose • questions about virtual corridores (VC) • uder what conditions • interactions of bfs hilltopping behavior and topograhpy • emergence of virtusl corridores – relatively nerrow paths bfs move • variabiity in bf. strategy affects formation of VCs

Entities, State Variables and Scales • Entities: – butterflies – square patches of land – • State Variables: – elevation – land – positions of butterflies on patches – x, y coordinates • Scales: – time and patch not impotant but – time length – time fo fly 25 -35 meters – patch size 25 x 25 meters • 1000 time steps with a 150 x 150 square landscape

• • Process Overview and Schedulling Process – movement of the bfs. at each time bfs. move one step order of movements – not impotant no interraction among bfs.

Design Concepts • basic principle - virtual corridores • emergence – how corridores emerge from – 1 - adaptive movement behavior of bfs – 2 – topograhy of landscape • adaptive behavior – moving behavior of butterflies based on an emprical law • objective, learning, prediction – not included

Design Concepts (cont. ) • sensing – how bfs percive higher elevation • interraction – not included • stocasticity – – each bf. at each step move uphill its neighbors with probability q and – move random to its neighbors with probability 1 -q

Initilization • • topography of the landscape 1 - artificial 2 - real values from a file 500 bfs set to a patch

Input Data • Environment is not chaning • not needed

Submodels • movement submodel: – how bfs decide to move • uphill: highest neigboring patch • random: randomly on of the eight naighboring pathces • For each butterfly at each time step • whether move uphill or random is by a contol parameter q • q: global variable from a uiform distribution

Submodels (cont. ) • at each time step • each bf draws a random variable x • from a uniform distribution between 0. 0 and 1. 0 if x < q move uphill otherwise move randomly

From ODD to Net. Logo Implementation • Purpose – information tab model description • Entities, State variables and Scales • tutles-own [ ] • patches-own [ ] • globals [ ]

From ODD to Net. Logo Implementation • Process and Schedule – go • Design concepts • Initilization - setup • Input data – from file input • Submodels - processes called from go

Entities State Variables Scales globals [] turtles-own [] patches-own [elevation] For a 150 x 150 lanscape from settings – corner – buttom left max-pxcor 149, max-pycor 149 Square landscape – turn off world wrapper patch size 3 or so

Initialization to setup ca ask patches [ ] reset-ticks end Templeate for initialization

Initialization – set elevations ask patches [ let elev 1 100 - distancexy 30 30 let elev 2 50 - distancexy 120 100 ifelse elev 1 > elev 2 [ set elevation elev 1] [ set elevation elev 2] set pcolor scale-color green elevation 0 100 ]

Initialization – set elevations elev 1 elev 2 local variables for creating two hills hill 1 at 30 30 at a height of 100 hill 2 at 120 100 at a height of 50 distancexy set pcolor scale-color green elevation 0 100 Scales color scale-color

Initialization - turtles crt 1 [ set sıze 2 setxy 85 95 ] create one turtle at 85 95 with a size of 2

Process Schedule to go ask turtles [move] tick if ticks >= 1000 [stop] end to move end in go procedure primitives tick, ticks stop

Submodels - move to move ifelse random-float 1 < q [uphill elevation] [move-to one-of neighbors] end

Submodels - move probability q uphill with 1 -q to random neighbor uphill move-to one-of define and initilize q

Chapter 5 of IABM 1. 2. 3. 4. Introduction Observation of Corridors Analazing the Model Time Series Resutls: Adding Plots and File Output 5. A Real Landscape 6. Summary and Conclusions

5. 1 Introduction • modeling – not formulating and implementing • iterative process – modifying refining model

The Problem • Problem: – where and how corridors are formed? – quantitative outputs to be analized – replace artificial landscape with a real topography

Learning Objectives • version control • quantitative outputs and simulation experiments • slider or switchs for global variables, reporters • output window, time series plot, exporting to files • importing data from a file

5. 2 Observation of Corridors • How to caracterize a corridore? • if all bfs have the same path: – start from same posstion and q = 1. 0 – corridor - very nerrow • if movement – completely random – q = 0. 0 – no corridore like feature • How width of paths change as q or topography varies

quantifying width • bfs can start and end – different places • Assume: – bfs stop – rich a local hilltop – – a patch higher then all its neighboringpatches • quantify width of the corridor – all bfs – #pathces visited – any bf divided by – mean distance – starting and edning locations – all bfs

quantifying width • lower bound 1. 0 when all bfs follow a streigth line • increases as bfs diverge • Analysis: – plot q v. s. corridor width

First modifications • slider for q – from 0. 0 to 1. 0 with increments 0. 01 • modify setup – create 50 bfs starting from same position • experiment with different q values • Programming Notes: moving variables to the interface – remove from globals – remove initialization in setup procedure – indicate with a comment

modifying move • bfs stop when they rich a local hill – a patch with an elevation higher then its neighbors – stop rest of the move procedure • code – start of the move if elevation >= [elevation] of max-one-of neighbors [elevation] [stop] • if condition ; turtle context [stop] move - in turtle context turtles get patch veriable - elevation

right side of condition • of and max-one-of commands: • of: [reporter or agent variable] of agent or agentset

right side of condition • agent variable: elevation • agent: agent in the neighborhood of the current turtle with maximum elevation max-one-of agentset [reporter or agent variable] • report an agent from the agentset based on the reporters value

width of the bf population • a - # of patches visited • b- mean distanc between bfs starting and ending positions • two new state variables – for each patch – keep track of whether a turtle visited – for each turtle – store its starting patch

width of the bf population • Add a boolean variable to pathces – used? patchs-own [used? ] – turn to true is the patch is ever visited

width of the bf population • Add a variable to turtles – startpatch turtles-own [start-patch] – set to the start patch when inilizing bfs

initilize in setup ask patches [. . . set used? false ] create-turtles [. . . set start-patch-here ] • patch-here: reports the patch the turtle is currently on • Programming note: initializing variables – all variables has an initial value of 0

move and go procedure • When a bf moves to a patch – set the patch variable to true – add end of move • in the go procedure before the program stops let final-corridor-width corridorwidth • a laocal variable is assigned the value of the corridor width computed by another procedure (reporter) to-report corridor-width • calculate and report corridor width • print the value of final-corridor-width to an output

go procedure to go ask turtles [move] tick if ticks >= 1000 [ let final-corridor-width output-print word "corridor width " final-corridor-width stop ] end

corridor-width reporter to-report corridor-width let patches-visited count patches with [used? ] let mean-distance mean [distance start-patch] of turtles report patches-visited / mean -distance

move to move if elevation >= [elevation] of max-one-of neighbors [elevation] [stop] ifelse random-float 1 < q [uphill elevation] [move-to one-of neighbors] set used? true end

5. 3 Analazing the Model • How corridor width output is affected from q • plot corridor width v. s. q • as q increases – corridor width falls as expected • but when q=1. 0 corridor widthis <1. 0 • How can this be?

5. 4 Time Series Resutls: Adding Plots and File Output to go ask turtles [move] plot corridor-width if ticks >= 1000 [. . . stop] end add a ploter to tthe interface give plot name “corridor width” write the results of plots to a file export-plot “corridor width” word “corridor-output-for-q ” q

exporting plots to a file • add the command to the end of go before the program stops export-plot “corridor width” word “corridor-output-for-q” q export-ploter_name filr_name

5. 5 A Real Landscape • real data from “Elevation. Data. txt” • from books web side • Programming Note: – grid-based: x-coordinate, y-coordinate and a value – one data line for each grid point

add to setup file-open “Elevation. Data. txt” while [not file-at-end? ] [ let next-x file-read let next-y file-read let next-elevation file-read ask patch next-x next-y [set elevation next-elevation] ] file-close

next do • determine dimensions of the world examining the data file • adjust the scale of the color for the new max and min values of the elevations • initial positions of bfs in a 10 x 10 area – randomly asign xcor and ycor of bfs setxy (80 + radnom 10) (90 + radnom 10)

scaling color let min-elevation min [elevation] of patches let max-elevation max [elevation] of patches ask patches [ set pcolor scale-color green elevation minelevation max-elevation set used? false ]

5. 6 Summary and Conclusions • Net. Logo for agent-based science • Modeling a system of multiple agents – quantitative variables – analyzing ouputs – simulation experiments – real spatial data

5. 6 Summary and Conclusions (cont. ) • butterfly model – simple but. . . • other environments – movement of ideas people – social networks – economic or political lanscapes