extensions [ nw ] globals [ policy_effect gradeAVG knowAVG gradeNAVG gradeSBMAVG gradeSDSBM gradeSDN knowNAVG knowSBMAVG ] breed [ professors professor ] breed [ grade_students grade_student ] ;the students who's main ambition is to maximize grades, regardless of knowledge breed [ know_students know_student ] ;the students who's main ambition is to maximize knowledge breed [ pass_students pass_student ] ;the students who's main ambition is to pass (grade >= 18) undirected-link-breed [ SBM-networks SBM-network ] ;Student black market links, spreading unofficial material undirected-link-breed [ link-networks link-network ] ;These links represents "positive" collaboration between students directed-link-breed [ Pro_networks Pro_network ] ;Professors' links to students SBM-networks-own [ numberof ] link-networks-own [ numberof2 ] turtles-own [ net_alt net_social net_time networking SBM_networking pro_networking ] know_students-own [ SBMmaterial SBMgrade Ngrade SBMknowledge Nknowledge Nknowledge-1 pro_contact ] grade_students-own [ SBMmaterial SBMgrade Ngrade SBMknowledge Nknowledge Nknowledge-1 pro_contact ] pass_students-own [ SBMmaterial SBMgrade Ngrade SBMknowledge Nknowledge Nknowledge-1 pro_contact ] professors-own [ creativity available exam socratic ] to setup ;Here we define the initial values of students' propensities to collaborate in the two types of collaboration and clear-all ;the professors' propensity to help students by interaction. The values depend to an extent randomly on the students (randomly assigned below) setup-turtles ;levels of sociality, having time, being altruistic, plus the type of exam and some professor charactheristics. Professors propensity to setup-patches ;interact depends on their levels of Socratic approach, availability and creativity. reset-ticks ask turtles with [shape = "person"] [ set networking random(100 + net_social + net_time + net_alt + Socratic_approach - Scholarships)* 0.1 set SBM_networking random(100 + net_social - net_time + exam_type - Socratic_approach + Scholarships - Official_material)* 0.1] ask professors [ set pro_networking random(10 + Socratic_approach + availability + Creativity_level)* 0.1] reset-ticks end to setup-patches ask patches [ set pcolor gray ] end to setup-turtles ;Here the students and professors are created. It's random how many of pass, grade, and know students there will be with create-grade_students 5 + random(10) + Sample_of_students ;a minimum of 5 per group. There will always be at least 1 professor. With the sliders the user create-know_students 5 + random(10) + Sample_of_students ;can decide higher or lower number of students and professors. create-pass_students 5 + random(10) + Sample_of_students create-professors 1 + random (7) + Sample_of_professors ask turtles [ set size 1 ] ask grade_students ;The color and shape of the grade_student is set [ set shape "person" set color 85] ask know_students ;Same as above but for knowledge students [ set shape "person" set color 95] ask pass_students ;Same as above but for pass students [ set shape "person" set color 105] ask professors [ set shape "person graduate" setxy random-xcor random-ycor set color 125 set networking 0 set SBM_networking 0 set available availability set socratic Socratic_approach ;Professors' charactheristics can be changed throught the interface to create different environments for the students set creativity Creativity_level] ask turtles with [shape = "person"] [ ;This is where the intial endowment of students' charactheristics is randomly set. In a way we are creating individuals. set net_alt random(10) set net_social random(10) set net_time random(10) set Ngrade 0 set SBMgrade 0 set Nknowledge-1 1 + random(10) set Nknowledge Nknowledge-1 + random(10) set SBMknowledge 1 + random(10) setxy random-xcor random-ycor ] end to go move invite_to_SBMnetwork invite_to_network invite_to_Pro_network do_plot tick if Time? [if ticks >= 20 [stop] ] ;activate the switch if you want only 20 exams, which would model a generic master program end to move ;For every step they take, student's gain knowledge. Knowledge students gain twice as much. ask turtles with [shape = "person"] [ forward random(10) set Nknowledge Nknowledge + 1 set SBMknowledge SBMknowledge + 1] ask professors [ forward random(10)] end to invite_to_network ;This is how students decide whether to interact in the "positive" collaboration. It depends on a threshold level for ask grade_students [ if networking > 10 ;their and their colleagues' networking propensity [ create-link-networks-with other turtles with [networking > 20] in-radius random(100) [set color pink]] ;grade_students are more likely to interact obtain_Nknowledge] ask pass_students [ if networking > 30 [ create-link-networks-with other turtles with [networking > 35] in-radius random(100) [set color pink]] ;positive network links have the color pink obtain_Nknowledge] ask know_students [ if networking > 30 [ create-link-networks-with other turtles with [networking > 35] in-radius random(100) [set color pink]] obtain_Nknowledge] end to invite_to_SBMnetwork ;This is how students decide whether to interact in the black market. It depends on a threshold level for ask grade_students [ if SBM_networking > 10 ;their and their colleagues' SBM-networking propensity [ create-SBM-networks-with other turtles with [SBM_networking > 20] in-radius random(100) [set color black]] obtain_SBMknowledge] ask pass_students [ if SBM_networking > 30 [ create-SBM-networks-with other turtles with [SBM_networking > 35] in-radius random(100) [set color black]] ;SBM-network links have the color black obtain_SBMknowledge] ask know_students [ if SBM_networking > 30 [ create-SBM-networks-with other turtles with [SBM_networking > 35] in-radius random(100) [set color black]] obtain_SBMknowledge] end to invite_to_Pro_network ;Professors decide whether to interact with students depending on their pro_networking and the students networking propensity, ask professors [ if pro_networking > 10 [ ;according to another threshold. The students who interact with professors create-Pro_networks-to turtles with [ networking > 35 ] [set color green + 10]] ;will gain pro_contact which enters positively into their Ngrade both directly (in obtain_Ngrade) ask out-link-neighbors [set pro_contact pro_contact + random(20) ;and indirectly through Nknowledge (in obtain_Nknowledge). obtain_Nknowledge]] if random-float(500) < 100 [ ask pro_networks [die]] ;The links to professors will disappear with a random chance end to obtain_Nknowledge set Nknowledge Nknowledge + pro_contact * 0.1 + 0.25 * (((Nknowledge - Nknowledge-1) / Nknowledge-1)) ;Knowledge is a function of contact with the professors and the growth rate if Nknowledge > 100 [ set Nknowledge 100 ] ;of knowledge. We make the assumption that the domain of the function is bounded if Nknowledge < 1 [set Nknowledge 1 ] ;in the interval [ 1 , 100 ]. obtain_Ngrade end to obtain_Ngrade ;The grade obtained as a result of positive interaction is a function of the student's level of Nknowledge and SMBknowledge, contact with professors, set Ngrade 0 ;how much official material they have access to and the level of professors' Socratic approach. We added random positive and negative elements that if Nknowledge > 75[ ;represents good and bad "luck". Students with a initial greater level of knowledge (when taking the exam) will have a greater coefficient. set Ngrade Ngrade + random(3 * Nknowledge + SBMknowledge + pro_contact + Official_material + Socratic_approach) * 0.5 - random(2) + random(2)] if Nknowledge < 75 [ set Ngrade Ngrade + random(2 * Nknowledge + SBMknowledge + pro_contact + Official_material + Socratic_approach) * 0.2 - random(5) + random(5)] if Ngrade > 30 [ set Ngrade 30 ] ;Grade's domain is bounded between 0 and 30. if Ngrade < 0 [ set Ngrade 0 ] ask pass_students [if Ngrade >= 18 [ set networking networking + 10 + random(50)]] ;Pass students will have a higher networking propensity if their grade is >= 18 and lower if not. if Ngrade <= 18 [ set networking random(10) set networking networking - 10 - random(100)] ask grade_students [if Ngrade >= 27 [ set networking networking - Scholarships + 10 + random(50)] ;Grade students will have a higher networking propensity if their grade is >= 27 and lower if not. if Ngrade <= 27 [ set networking random(50) set networking networking - 10 - random(100)]] ask know_students [if Ngrade >= 25 and Nknowledge > 100 [ set networking networking + 10 + random(50)] ;Knowledge students will have a higher networking propensity if their grade is >= 25 and lower if not. if Ngrade <= 25 and Nknowledge < 100 [ set networking random(10) set networking networking - 10 - random(50)]] evaluate end to obtain_SBMknowledge ;Participating in a SBM network have a negative impact on SBMknowledge but will give students set SBMmaterial 0 ;a higher level of SBM material which enters SBMgrade positively. SBMmaterial is reset before each exam. set SBMmaterial SBMmaterial + random(10) set SBMknowledge SBMknowledge + 0.2 * SBMmaterial - (((Nknowledge - Nknowledge-1) / Nknowledge-1)) if SBMknowledge > 100 [set SBMknowledge 100] if SBMknowledge < 1 [set SBMknowledge 1] obtain_SBMgrade end to obtain_SBMgrade ;Students obtain their Ngrades as a function of the exam type, how much SBMmaterial they have and some random "luck" elements. set SBMgrade 0 ;We can assume an exponential path WLOG. set SBMgrade SBMgrade + exp(random(15) - 0.1 * exam_type + 0.25 * SBMmaterial) + random(10) - random(10) if SBMgrade > 30 [ set SBMgrade 30 ] if SBMgrade < 0 [ set SBMgrade 0 ] ask pass_students [if SBMgrade >= 18 [ set SBM_networking SBM_networking + random(10) + 0.5 * SBMknowledge] ;Pass students will have a higher SBM-networking propensity if their grade is >= 18 and lower if not. if SBMgrade <= 18 [ set SBM_networking random(40) set SBM_networking SBM_networking - random(40)]] ask grade_students [if SBMgrade >= 27 [ set SBM_networking SBM_networking + Scholarships + random(10) + 0.5 * SBMknowledge] ;Grade students will have a higher SBM-networking propensity if their grade is >= 27 and lower if not. if SBMgrade <= 27 [ set SBM_networking random(10) set SBM_networking SBM_networking - random(40)]] ask know_students [if SBMgrade >= 25 [ set SBM_networking SBM_networking + random(10) + 0.5 * SBMknowledge] ;Know students will have a higher SBM-networking propensity if their grade is >= 25 and lower if not. if SBMgrade <= 25 [ set SBM_networking random(40) set SBM_networking SBM_networking - random(40)]] evaluate end to evaluate ;After participating in a network and taking an exam there is a 10 % chance that they evaluate whether to if random-float(1000) < 100 [ ;leave the network depending on results related to grade and knowledge (for the knowledge students) ask pass_students[ if Ngrade < 18 [ask my-link-networks [die]]] ask pass_students[ if SBMgrade < 18 [ask my-SBM-networks [die]]] ask know_students[ if Ngrade < 25 and Nknowledge < 10 [ask my-link-networks [die] ]] ask know_students[ if SBMgrade < 25 and SBMknowledge < 10 [ask my-SBM-networks [die]]] ask grade_students[ if Ngrade < 27 [ask my-link-networks [die]]] ask pass_students[ if SBMgrade < 27 [ask my-SBM-networks [die]]]] end to l-circle ;Layout the turtles in a circle for a nice overview, useful when controlling the results of betweennesses and clustering ask grade_students [ set label Ngrade ] layout-circle sort-on [ Ngrade ] grade_students max-pxcor * 0.9 ask pass_students [ set label Ngrade ] layout-circle sort-on [ Ngrade ] pass_students max-pxcor * 0.9 ask know_students [ set label Ngrade] layout-circle sort-on [ Ngrade ] know_students max-pxcor * 0.9 ask professors[ set label pro_networking ] layout-circle sort-on [ pro_networking ] professors max-pxcor * 0.45 end to do_plot ;Obtains the values we need for plotting and printing the output (if you're interested in SD of a specific group of students set gradeSBMAVG mean [SBMgrade] of turtles with [shape = "person"] ;just remove the ";" in front of it and instead put it in front of the other groups and the first row. ;set gradeSBMAVG mean [SBMgrade] of grade_students ;set gradeSBMAVG mean [SBMgrade] of know_students ;set gradeSBMAVG mean [SBMgrade] of pass_students set gradeSDSBM standard-deviation [SBMgrade] of turtles with [shape = "person"] ;set gradeSDSBM standard-deviation [SBMgrade] of grade_students ;set gradeSDSBM standard-deviation [SBMgrade] of know_students ;set gradeSDSBM standard-deviation [SBMgrade] of pass_students set gradeNAVG mean [Ngrade] of turtles with [shape = "person"] ;set gradeNAVG mean [Ngrade] of grade_students ;set gradeNAVG mean [Ngrade] of know_students ;set gradeNAVG mean [Ngrade] of pass_students set gradeSDN standard-deviation [Ngrade] of turtles with [shape = "person"] ;set gradeSDN standard-deviation [Ngrade] of grade_students ;set gradeSDN standard-deviation [Ngrade] of know_students ;set gradeSDN standard-deviation [Ngrade] of pass_students set knowNAVG mean [Nknowledge] of turtles with [shape = "person"] ;set knowNAVG mean [Nknowledge] of grade_students ;set knowNAVG mean [Nknowledge] of know_students ;set knowNAVG mean [Nknowledge] of pass_students set knowSBMAVG mean [SBMknowledge] of turtles with [shape = "person"] ;set knowSBMAVG mean [SBMknowledge] of grade_students ;set knowSBMAVG mean [SBMknowledge] of know_students ;set knowSBMAVG mean [SBMknowledge] of pass_students output-print gradeNAVG output-print knowNAVG output-print gradeSBMAVG output-print knowSBMAVG let n_links count link-networks if n_links < 1 [ set n_links 1 ] let SBM_links count SBM-networks if SBM_links < 1 [ set SBM_links 1 ] ;Policy effect is the general result of policy investments in knowledge. if ticks > 1 [set policy_effect ((knowNAVG * (n_links / (n_links + SBM_links))) + (knowSBMAVG * (SBM_links / (n_links + SBM_links))) ) ] end to betweenness ;Calculates the betweenesses-centrality nw:set-context turtles links ask turtles [ let res0 nw:betweenness-centrality if is-number? res0 [set label res0 set label precision res0 5]] end to clustering ;Calculates the local clustering nw:set-context turtles link-networks ask turtles [ let res2 nw:clustering-coefficient set label res2 set label precision res2 5] end @#$#@#$#@ GRAPHICS-WINDOW 526 10 965 470 16 16 13.0 1 10 1 1 1 0 1 1 1 -16 16 -16 16 0 0 1 ticks 30.0 BUTTON 7 10 71 43 NIL Setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 71 10 134 43 NIL Go T 1 T OBSERVER NIL NIL NIL NIL 1 SLIDER 6 44 178 77 Scholarships Scholarships 0 100 0 1 1 NIL HORIZONTAL SLIDER 5 172 177 205 Exam_Type Exam_Type -100 100 100 1 1 NIL HORIZONTAL SLIDER 5 206 177 239 availability availability 0 100 100 1 1 NIL HORIZONTAL SLIDER 5 238 177 271 Socratic_approach Socratic_approach 0 100 100 1 1 NIL HORIZONTAL SLIDER 5 89 177 122 Official_material Official_material 0 100 100 1 1 NIL HORIZONTAL SLIDER 5 138 177 171 Creativity_level Creativity_level 0 100 100 1 1 NIL HORIZONTAL BUTTON 407 223 505 256 layout-circle l-circle NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 407 189 504 222 NIL clustering NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 136 10 199 43 NIL Go NIL 1 T OBSERVER NIL NIL NIL NIL 1 OUTPUT 1017 406 1224 469 11 PLOT 0 367 254 517 Networks: Grade & Knowledge Time NIL 0.0 10.0 0.0 110.0 true false "" "" PENS "Mean SBMgrade" 1.0 0 -2064490 true "" "plot gradeNAVG" "Mean Nknowledge" 1.0 0 -10899396 true "" "plot knowNAVG" PLOT 255 367 507 517 Black market: Grade & Knowledge NIL NIL 0.0 10.0 0.0 110.0 true false "" "" PENS "default" 1.0 0 -16777216 true "" "plot gradeSBMAVG" "pen-1" 1.0 0 -10899396 true "" "plot knowSBMAVG" PLOT 1016 167 1216 317 Grade comparision NIL NIL 0.0 10.0 0.0 10.0 true false "" "" PENS "default" 1.0 0 -2064490 true "" "plot gradeNAVG" "pen-1" 1.0 0 -16777216 true "" "plot gradeSBMAVG" BUTTON 407 154 512 187 NIL betweenness NIL 1 T OBSERVER NIL NIL NIL NIL 1 MONITOR 0 322 120 367 NIL count link-networks 17 1 11 MONITOR 255 323 381 368 NIL count SBM-networks 17 1 11 PLOT 1015 14 1215 164 Knowledge comparision NIL NIL 0.0 10.0 0.0 10.0 true false "" "" PENS "default" 1.0 0 -2064490 true "" "plot knowNAVG" "pen-1" 1.0 0 -16777216 true "" "plot knowSBMAVG" TEXTBOX 970 413 1025 469 Ngrade\nNknow\nSBMgrade\nSBMknow 10 0.0 1 TEXTBOX 180 88 355 140 Official material is a discrete scale from 1 up to 100 of units of material given as an endownment to students 10 0.0 1 TEXTBOX 181 45 331 84 Scholarship is an index of the current scholarship available in the market 10 0.0 1 TEXTBOX 184 136 393 281 These sliders represent indexes related to:\n1. The creativity proper of professors\n2. The path dependence of new exams on previous questions. As the index goes towards 100% the path dependence is total and therefore the exam is perfectly forcastable by students with SBM-material\n3. The average availability for solving students' doubts \n4. The relevance of the Socratic method as personal teaching methodology\n 10 0.0 1 MONITOR 1017 350 1109 395 NIL gradeSDSBM 2 1 11 TEXTBOX 1017 325 1167 351 Standard deviation of SBM-grades 10 0.0 1 MONITOR 130 323 254 368 NIL count Pro_networks 17 1 11 MONITOR 1131 350 1200 395 NIL gradeSDN 2 1 11 TEXTBOX 1131 325 1258 352 Standard deviation of N-grades 10 0.0 1 PLOT 363 10 523 134 Policy effect NIL Knowledge 0.0 10.0 0.0 100.0 true false "" "" PENS "default" 1.0 0 -13345367 true "" "plot policy_effect" TEXTBOX 224 18 374 36 NIL 11 0.0 1 SLIDER 59 285 231 318 Sample_of_students Sample_of_students 0 25 0 1 1 NIL HORIZONTAL SLIDER 233 285 406 318 Sample_of_professors Sample_of_professors 0 10 0 1 1 NIL HORIZONTAL SWITCH 201 10 304 43 Time? Time? 1 1 -1000 @#$#@#$#@ ## WHAT IS IT? With this model we try to simulate different possibile types of relations within the University system affecting the process of grading students and increasing their knowledge. ## HOW IT WORKS There are three types of students associated with different aims and a one single type of professor whose characteristics are chageble by the user in the interface. ## HOW TO USE IT Professor's and environmental characteristics are modifible in the interface, while an initial set of agents with randomized characteristics is created by the authors. ## THINGS TO NOTICE On the right side of the interface the output of grade and knowledge is presented in a time series analysis. ## EXTENDING THE MODEL In a broader area, it would be interesting opening the makerts barriers to the labor market. In this way the relation of knowledge and grades may be seen in a context of theory of signals for employers and employees (Stiglitz (2001) ). @#$#@#$#@ default true 0 Polygon -7500403 true true 150 5 40 250 150 205 260 250 airplane true 0 Polygon -7500403 true true 150 0 135 15 120 60 120 105 15 165 15 195 120 180 135 240 105 270 120 285 150 270 180 285 210 270 165 240 180 180 285 195 285 165 180 105 180 60 165 15 arrow true 0 Polygon -7500403 true true 150 0 0 150 105 150 105 293 195 293 195 150 300 150 box false 0 Polygon -7500403 true true 150 285 285 225 285 75 150 135 Polygon -7500403 true true 150 135 15 75 150 15 285 75 Polygon -7500403 true true 15 75 15 225 150 285 150 135 Line -16777216 false 150 285 150 135 Line -16777216 false 150 135 15 75 Line -16777216 false 150 135 285 75 bug true 0 Circle -7500403 true true 96 182 108 Circle -7500403 true true 110 127 80 Circle -7500403 true true 110 75 80 Line -7500403 true 150 100 80 30 Line -7500403 true 150 100 220 30 butterfly 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165 195 line true 0 Line -7500403 true 150 0 150 300 line half true 0 Line -7500403 true 150 0 150 150 pentagon false 0 Polygon -7500403 true true 150 15 15 120 60 285 240 285 285 120 person false 0 Circle -7500403 true true 110 5 80 Polygon -7500403 true true 105 90 120 195 90 285 105 300 135 300 150 225 165 300 195 300 210 285 180 195 195 90 Rectangle -7500403 true true 127 79 172 94 Polygon -7500403 true true 195 90 240 150 225 180 165 105 Polygon -7500403 true true 105 90 60 150 75 180 135 105 person graduate false 0 Circle -16777216 false false 39 183 20 Polygon -1 true false 50 203 85 213 118 227 119 207 89 204 52 185 Circle -7500403 true true 110 5 80 Rectangle -7500403 true true 127 79 172 94 Polygon -8630108 true false 90 19 150 37 210 19 195 4 105 4 Polygon -8630108 true false 120 90 105 90 60 195 90 210 120 165 90 285 105 300 195 300 210 285 180 165 210 210 240 195 195 90 Polygon -1184463 true false 135 90 120 90 150 135 180 90 165 90 150 105 Line -2674135 false 195 90 150 135 Line -2674135 false 105 90 150 135 Polygon -1 true false 135 90 150 105 165 90 Circle -1 true false 104 205 20 Circle -1 true false 41 184 20 Circle -16777216 false false 106 206 18 Line -2674135 false 208 22 208 57 plant false 0 Rectangle -7500403 true true 135 90 165 300 Polygon -7500403 true true 135 255 90 210 45 195 75 255 135 285 Polygon -7500403 true true 165 255 210 210 255 195 225 255 165 285 Polygon -7500403 true true 135 180 90 135 45 120 75 180 135 210 Polygon -7500403 true true 165 180 165 210 225 180 255 120 210 135 Polygon -7500403 true true 135 105 90 60 45 45 75 105 135 135 Polygon -7500403 true true 165 105 165 135 225 105 255 45 210 60 Polygon -7500403 true true 135 90 120 45 150 15 180 45 165 90 sheep false 15 Circle -1 true true 203 65 88 Circle -1 true true 70 65 162 Circle -1 true true 150 105 120 Polygon -7500403 true false 218 120 240 165 255 165 278 120 Circle -7500403 true false 214 72 67 Rectangle -1 true true 164 223 179 298 Polygon -1 true true 45 285 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Polygon -7500403 true true 150 30 15 255 285 255 triangle 2 false 0 Polygon -7500403 true true 150 30 15 255 285 255 Polygon -16777216 true false 151 99 225 223 75 224 truck false 0 Rectangle -7500403 true true 4 45 195 187 Polygon -7500403 true true 296 193 296 150 259 134 244 104 208 104 207 194 Rectangle -1 true false 195 60 195 105 Polygon -16777216 true false 238 112 252 141 219 141 218 112 Circle -16777216 true false 234 174 42 Rectangle -7500403 true true 181 185 214 194 Circle -16777216 true false 144 174 42 Circle -16777216 true false 24 174 42 Circle -7500403 false true 24 174 42 Circle -7500403 false true 144 174 42 Circle -7500403 false true 234 174 42 turtle true 0 Polygon -10899396 true false 215 204 240 233 246 254 228 266 215 252 193 210 Polygon -10899396 true false 195 90 225 75 245 75 260 89 269 108 261 124 240 105 225 105 210 105 Polygon -10899396 true false 105 90 75 75 55 75 40 89 31 108 39 124 60 105 75 105 90 105 Polygon -10899396 true false 132 85 134 64 107 51 108 17 150 2 192 18 192 52 169 65 172 87 Polygon -10899396 true false 85 204 60 233 54 254 72 266 85 252 107 210 Polygon -7500403 true true 119 75 179 75 209 101 224 135 220 225 175 261 128 261 81 224 74 135 88 99 wheel false 0 Circle -7500403 true true 3 3 294 Circle -16777216 true false 30 30 240 Line -7500403 true 150 285 150 15 Line -7500403 true 15 150 285 150 Circle -7500403 true true 120 120 60 Line -7500403 true 216 40 79 269 Line -7500403 true 40 84 269 221 Line -7500403 true 40 216 269 79 Line -7500403 true 84 40 221 269 wolf false 0 Polygon -16777216 true false 253 133 245 131 245 133 Polygon -7500403 true true 2 194 13 197 30 191 38 193 38 205 20 226 20 257 27 265 38 266 40 260 31 253 31 230 60 206 68 198 75 209 66 228 65 243 82 261 84 268 100 267 103 261 77 239 79 231 100 207 98 196 119 201 143 202 160 195 166 210 172 213 173 238 167 251 160 248 154 265 169 264 178 247 186 240 198 260 200 271 217 271 219 262 207 258 195 230 192 198 210 184 227 164 242 144 259 145 284 151 277 141 293 140 299 134 297 127 273 119 270 105 Polygon -7500403 true true -1 195 14 180 36 166 40 153 53 140 82 131 134 133 159 126 188 115 227 108 236 102 238 98 268 86 269 92 281 87 269 103 269 113 x false 0 Polygon -7500403 true true 270 75 225 30 30 225 75 270 Polygon -7500403 true true 30 75 75 30 270 225 225 270 @#$#@#$#@ NetLogo 5.1.0 @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ default 0.0 -0.2 0 0.0 1.0 0.0 1 1.0 0.0 0.2 0 0.0 1.0 link direction true 0 Line -7500403 true 150 150 90 180 Line -7500403 true 150 150 210 180 @#$#@#$#@ 0 @#$#@#$#@