;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; James March's Organisational Learning Model ; Based on March (1991) and on BASIC version (mostly by March) supplied by Simon Rodan (Thanks!) ; This NetLogo version (C) Christopher J Watts, 2011 ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;extensions [matrix] globals [ reality superior-group belief-sums num-bupdates ; # changes made to beliefs num-cupdates ; # changes made to codes equilibrium ; Are we at equilibrium yet? num-alt ; # workers with alternative socialization (e.g. fast) mean-cscore mean-wscore mean-cknowledge mean-wknowledge mean-s-wknowledge mean-as-wknowledge mean-wsocialization ] breed [workers worker] breed [orgs org] directed-link-breed [wlinks wlink] ; x works for y workers-own [ beliefs w-score w-knowledge wsocialization cur-org ] orgs-own [ code code-score code-knowledge ] ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to setup clear-all set reality n-values number-of-dimensions [(2 * (random 2)) - 1] ; Initialised to 1 or -1 set superior-group nobody set belief-sums n-values number-of-dimensions [0] ; Setup organizations create-orgs number-of-organizations [ set hidden? true set shape "square" set code n-values number-of-dimensions [0] ] ; Setup workers set num-alt int (number-of-workers * proportion-alt-socialization / 100) ; i.e. # fast socialised create-workers num-alt [ set hidden? true set wsocialization alt-socialization ] create-workers (number-of-workers - num-alt) [ ; i.e. slow or normal socialised set hidden? true set wsocialization socialization ] ask workers [ set shape "person" set beliefs n-values number-of-dimensions [(random 3) - 1] ; Initialised to 1, 0 or -1 set cur-org one-of orgs create-wlink-to cur-org [ set hidden? true ] ] set equilibrium false set mean-wsocialization mean [wsocialization] of workers end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ; Order of events in March's version: ;For each time period ; Turmoil / Turbulence ; Turnover ; Calculate Code Knowledge ; Calculate Agents Knowledge ; (These are the figures then output.) ; Calculate membership of Superior Group ; socialization ; Learning ; Output Knowledge figures (as calculated earlier) ;Next time period to go if ticks >= max-ticks [stop] ; Turmoil / Turbulence set reality map [ifelse-value (turbulence > random-float 100) [ifelse-value (? = 1) [-1] [1]] [?]] reality ; Turnover: worker left, to be replaced by one with random beliefs. ask workers [ if turnover > random-float 100 [ set beliefs n-values number-of-dimensions [(random 3) - 1] ; Reinitialised to 1, 0 or -1 ] ] calc-org-knowledge calc-worker-knowledge ; (These are the figures then output.) ;for each organization (if you have more than one) set num-bupdates 0 set num-cupdates 0 ask orgs [ calc-superior-group ; socialization let wsoc 0 ask in-wlink-neighbors [ set wsoc wsocialization set beliefs (map [socialised-belief ?1 ?2 wsoc] (beliefs) ([code] of cur-org)) ] ; calc-worker-knowledge ; I'm surprised March allowed socialization after the superior-group has been determined. ; calc-superior-group ; Learning set code (map [learned-code ?1 ?2] code belief-sums) ;next organization ] ; Output Knowledge figures (as calculated earlier) update-plots ;set equilibrium (0 = (num-bupdates + num-cupdates)) set equilibrium (0 = sum [diffs-from-code] of workers) if equilibrium and halt-on-equilibrium? [ calc-org-knowledge calc-worker-knowledge update-stats stop ] tick end to calc-org-knowledge ; Calculate Code Knowledge ask orgs [ ; NB: Knowledge is the proportion of dimensions that match reality (as per March's text), ; but Score is the sum of scoring 1 for a match, -1 for a mismatch, 0 for Undetermined, i.e. code-item * reality. set code-score sum (map [?1 * ?2] (reality) (code)) set code-knowledge sum (map [ifelse-value (?1 = ?2) [1] [0]] (reality) (code)) ] end to calc-worker-knowledge ; Calculate Agents Knowledge ask workers [ ; NB: Knowledge is the proportion of dimensions that match reality (as per March's text), ; but Score is the sum of scoring 1 for a match, -1 for a mismatch, 0 for Undetermined, i.e. belief * reality. set w-score sum (map [?1 * ?2] (reality) (beliefs)) set w-knowledge sum (map [ifelse-value (?1 = ?2) [1] [0]] (reality) (beliefs)) ] end to calc-superior-group ; Calculate membership of Superior Group set superior-group in-wlink-neighbors with [w-score > ([code-score] of myself)] ; set superior-group in-wlink-neighbors with [w-knowledge > ([code-knowledge] of myself)] set belief-sums n-values number-of-dimensions [0] ask superior-group [ set belief-sums (map [?1 + ?2] belief-sums beliefs) ] end to-report socialised-belief [bval cval wsoc] if cval = 0 [report bval] if bval = cval [report bval] if (wsoc > random-float 100) [ set num-bupdates num-bupdates + 1 if bval = 0 [report cval] report 0 ] report bval end to-report learned-code [cval bsum] let bsize abs bsum ; Calc majority view (of superior-group), if one exists. let bsign (ifelse-value (bsum = 0) [0] [bsum / bsize]) if cval = bsign [report cval] ; Majority view matches code. if bsize = 0 [report cval] ; No majority view. let cur-member 0 let new-val cval ifelse cval = 0 [ ; Move from 0 to bsign? while [(new-val != bsign) and (cur-member < bsize)] [ if (learning > random-float 100) [ set new-val bsign set num-cupdates num-cupdates + 1 ] set cur-member cur-member + 1 ] report new-val ] [ ; Move from opposite of bsign to 0? while [(new-val != 0) and (cur-member < bsize)] [ if (learning > random-float 100) [ set new-val 0 set num-cupdates num-cupdates + 1 ] set cur-member cur-member + 1 ] report new-val ] end to-report diffs-from-code report sum (map [ifelse-value (?1 = ?2) [0] [1]] beliefs ([code] of cur-org)) end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; to update-stats set mean-cscore (mean [code-score] of orgs) / number-of-dimensions set mean-wscore (mean [w-score] of workers) / number-of-dimensions set mean-cknowledge (mean [code-knowledge] of orgs) / number-of-dimensions set mean-wknowledge (mean [w-knowledge] of workers) / number-of-dimensions ifelse num-alt = 0 [ set mean-s-wknowledge (mean [w-knowledge] of workers with [wsocialization = socialization]) / number-of-dimensions set mean-as-wknowledge 0 ] [ ifelse num-alt = count workers [ set mean-s-wknowledge 0 set mean-as-wknowledge (mean [w-knowledge] of workers with [wsocialization = alt-socialization]) / number-of-dimensions ] [ set mean-s-wknowledge (mean [w-knowledge] of workers with [wsocialization = socialization]) / number-of-dimensions set mean-as-wknowledge (mean [w-knowledge] of workers with [wsocialization = alt-socialization]) / number-of-dimensions ] ] end to update-plots update-stats set-current-plot "Knowledge Evolution" set-current-plot-pen "Code" plotxy ticks mean-cknowledge set-current-plot-pen "Workers Mean" plotxy ticks mean-wknowledge set-current-plot "Updates" set-current-plot-pen "Codes" plotxy ticks num-cupdates / (number-of-dimensions * count orgs) set-current-plot-pen "Beliefs" plotxy ticks num-bupdates / (number-of-dimensions * count workers) end ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; @#$#@#$#@ GRAPHICS-WINDOW 8 360 180 553 1 1 54.0 1 10 1 1 1 0 1 1 1 -1 1 -1 1 0 0 1 ticks INPUTBOX 8 67 163 127 Number-Of-Dimensions 30 1 0 Number INPUTBOX 8 190 163 250 Number-Of-Workers 50 1 0 Number SLIDER 169 67 341 100 Socialization Socialization 0 100 50 1 1 NIL HORIZONTAL SLIDER 169 102 341 135 Learning Learning 0 100 50 1 1 NIL HORIZONTAL SLIDER 169 138 341 171 Turnover Turnover 0 100 0 1 1 NIL HORIZONTAL SLIDER 169 174 341 207 Turbulence Turbulence 0 100 0 1 1 NIL HORIZONTAL SLIDER 169 209 341 242 Alt-Socialization Alt-Socialization 0 100 90 1 1 NIL HORIZONTAL SLIDER 169 244 367 277 Proportion-Alt-Socialization Proportion-Alt-Socialization 0 100 0 1 1 NIL HORIZONTAL INPUTBOX 8 254 163 314 Max-ticks 200 1 0 Number BUTTON 8 320 72 353 Setup setup NIL 1 T OBSERVER NIL NIL NIL NIL BUTTON 75 320 138 353 Go go T 1 T OBSERVER NIL NIL NIL NIL TEXTBOX 10 10 384 43 James March's Organisational Learning Model 18 0.0 1 INPUTBOX 8 129 163 189 Number-Of-Organizations 1 1 0 Number PLOT 372 66 730 294 Knowledge Evolution Time (ticks) Knowledge 0.0 1.0 0.0 1.0 true true PENS "Code" 1.0 0 -16777216 true "Workers Mean" 1.0 0 -2674135 true TEXTBOX 7 36 257 64 This version (C) Christopher J Watts, 2011 11 0.0 1 MONITOR 372 323 447 368 Code Mean mean-cknowledge 3 1 11 MONITOR 450 323 545 368 Workers' Mean mean-wknowledge 3 1 11 TEXTBOX 372 306 522 324 Knowledge Statistics: 11 0.0 1 TEXTBOX 372 379 522 397 Socialisation Statistics: 11 0.0 1 MONITOR 371 397 484 442 Mean Socialization mean-wsocialization 1 1 11 SWITCH 169 279 335 312 Halt-On-Equilibrium? Halt-On-Equilibrium? 0 1 -1000 PLOT 371 449 732 648 Updates Time (ticks) # Changes (Standardized) 0.0 1.0 0.0 1.0 true true PENS "Codes" 1.0 0 -16777216 true "Beliefs" 1.0 0 -2674135 true MONITOR 371 652 477 697 # Code Changes num-cupdates 1 1 11 MONITOR 481 652 589 697 # Belief Changes num-bupdates 1 1 11 BUTTON 141 320 220 353 Go Once go NIL 1 T OBSERVER NIL NIL NIL NIL MONITOR 593 652 686 697 At equilibrium? equilibrium 17 1 11 MONITOR 550 396 692 441 # Workers above Code count superior-group 1 1 11 TEXTBOX 170 50 320 68 P1, P2, P3, P4: 11 0.0 1 TEXTBOX 554 304 704 322 Score Statistics: 11 0.0 1 MONITOR 553 323 628 368 Code Mean mean-cscore 3 1 11 MONITOR 631 323 726 368 Workers' Mean mean-wscore 3 1 11 TEXTBOX 550 380 700 398 Workers better than Code: 11 0.0 1 @#$#@#$#@ JAMES MARCH'S ORGANISATIONAL LEARNING MODEL ------------------------------------------- A NetLogo version of March's classic Organisation Learning Model, based on the description in March (1991) and BASIC code derived from March's original, supplied to me by Simon Rodan (thanks for that!). An organisation uses its workers to try to develop a coded form of knowledge of reality. The danger is that the population of workers will converge too quickly on a single view, matching the code, which fails to match reality. Slower learning processes may avoid this premature convergence. But too slow learning may also result in poor knowledge. A balance is needed between exploration of new views and exploitation of those already held. HOW IT WORKS ------------ An organisation has workers and exists in an environment ("reality"). Reality consists of a number of dimensions, each of which takes the value 1 or -1. Workers have beliefs, one for each dimension, initialised as 1, 0 or -1. The organisation has a code, representing its official view of reality, initialised as 0 (No opinion). Workers alter their beliefs under the influence of the code, as part of socialisation. The code is adapted to the beliefs of workers whose knowledge is currently superior to that of the code. There is a chance of Turnover, whereby a worker leaves to be replaced with one who has random beliefs. There is a chance of Turbulence, or "Turmoil", whereby a dimension of reality changes value. Workers may differ in their socialisation rates. A given proportion of them take an alternative socialisation rate. Both workers and the organisation codes have "knowledge" values, based on their relation to reality. (But see the comment below.) HOW TO USE IT ------------- March did not experiment with the numbers of organisations (1), workers (50), or dimensions (30). Choose parameter values for: Socialization (P1), a probability given as a percentage (i.e. values from 0 to 100) Learning (P2) Turnover (P3) Turbulence (P4) Alt-Socialisation : the alternative rate for socialisation Proportion-Alt-Socialisation : the proportion of workers who take the alternative value. Halt-On-Equilibrium? : Whether or not to halt the simulation when codes match the beliefs of workers. Max-ticks : Simulation runs halt when ticks reaches this value. THINGS TO NOTICE ---------------- There are BehaviorSpace experiments defined to try to reproduce the figures in March (1991). Qualitatively we can agree with most of what he writes. However, the scale is out for much of the parameter ranges. (E.g. See fig.1, high P2; fig.4, low P3.; fig.5, P3=10.) THINGS TO TRY ------------- One problem with the March model is the high variance in output metrics. This makes it difficult to compare results or prove that one parameter setting is better than another. March ran 80 simulation replications for each setting. The experiments could easily be run with more, but it is questionable whether this is sensible. Real life is run only once. A conclusion that only shows up after 10000 replications might be "statistically significant", but would not be important. Besides which, note what March says in the last third of the paper about variability in organisational performance. Confusion surrounds the definition (and use and calculation) of knowledge. March seems to write as if it is the proportion of dimensions for which beliefs or code match reality in value. However, the BASIC code seems to be a sum of (belief * reality) and sum of (code * reality). See also the formula given in Rodan (2005). At present, we use the sum products (which we call "score") to determine the superior-group of workers who can affect the code through learning. However, the proportion (call it "knowledge") is closer in scale to the values in March's figures. (The user is welcome to try other methods... Please let us know if you ever get close to March's results!) EXTENDING THE MODEL ------------------- Lots of attempts have been made (see references). Consider trying alternative definitions of knowledge, definitions of reality, social network structures between workers, multiple organisations competing for workers and knowledge. RELATED MODELS -------------- Consider instead Lazer & Friedman (2007) ASQ, which uses a variation on Kauffman's NK fitness landscapes to examine the role network structures play in controlling the risk of premature convergence. CREDITS AND REFERENCES ---------------------- March, James G. (1991) "Exploration and Exploitation in Organizational Learning". Organization Science, Vol. 2, No. 1, Special Issue: Organizational Learning: Papers in Honor of (and by) James G. March, pp. 71-87. Rodan, S., (2005), “Exploration and Exploitation Revisited: Extending March's Model of Mutual Learning”, Scandinavian Journal of Management, 21: 407-428. See also papers in: Academy of Management Journal, 49(4), August 2006. @#$#@#$#@ 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 true 0 Polygon -7500403 true true 150 165 209 199 225 225 225 255 195 270 165 255 150 240 Polygon -7500403 true true 150 165 89 198 75 225 75 255 105 270 135 255 150 240 Polygon -7500403 true true 139 148 100 105 55 90 25 90 10 105 10 135 25 180 40 195 85 194 139 163 Polygon -7500403 true true 162 150 200 105 245 90 275 90 290 105 290 135 275 180 260 195 215 195 162 165 Polygon -16777216 true false 150 255 135 225 120 150 135 120 150 105 165 120 180 150 165 225 Circle -16777216 true false 135 90 30 Line -16777216 false 150 105 195 60 Line -16777216 false 150 105 105 60 car false 0 Polygon -7500403 true true 300 180 279 164 261 144 240 135 226 132 213 106 203 84 185 63 159 50 135 50 75 60 0 150 0 165 0 225 300 225 300 180 Circle -16777216 true false 180 180 90 Circle -16777216 true false 30 180 90 Polygon -16777216 true false 162 80 132 78 134 135 209 135 194 105 189 96 180 89 Circle -7500403 true true 47 195 58 Circle -7500403 true true 195 195 58 circle false 0 Circle -7500403 true true 0 0 300 circle 2 false 0 Circle -7500403 true true 0 0 300 Circle -16777216 true false 30 30 240 cow false 0 Polygon -7500403 true true 200 193 197 249 179 249 177 196 166 187 140 189 93 191 78 179 72 211 49 209 48 181 37 149 25 120 25 89 45 72 103 84 179 75 198 76 252 64 272 81 293 103 285 121 255 121 242 118 224 167 Polygon -7500403 true true 73 210 86 251 62 249 48 208 Polygon -7500403 true true 25 114 16 195 9 204 23 213 25 200 39 123 cylinder false 0 Circle -7500403 true true 0 0 300 dot false 0 Circle -7500403 true true 90 90 120 face happy false 0 Circle -7500403 true true 8 8 285 Circle -16777216 true false 60 75 60 Circle -16777216 true false 180 75 60 Polygon -16777216 true false 150 255 90 239 62 213 47 191 67 179 90 203 109 218 150 225 192 218 210 203 227 181 251 194 236 217 212 240 face neutral false 0 Circle -7500403 true true 8 7 285 Circle -16777216 true false 60 75 60 Circle -16777216 true false 180 75 60 Rectangle -16777216 true false 60 195 240 225 face sad false 0 Circle -7500403 true true 8 8 285 Circle -16777216 true false 60 75 60 Circle -16777216 true false 180 75 60 Polygon -16777216 true false 150 168 90 184 62 210 47 232 67 244 90 220 109 205 150 198 192 205 210 220 227 242 251 229 236 206 212 183 fish false 0 Polygon -1 true false 44 131 21 87 15 86 0 120 15 150 0 180 13 214 20 212 45 166 Polygon -1 true false 135 195 119 235 95 218 76 210 46 204 60 165 Polygon -1 true false 75 45 83 77 71 103 86 114 166 78 135 60 Polygon -7500403 true true 30 136 151 77 226 81 280 119 292 146 292 160 287 170 270 195 195 210 151 212 30 166 Circle -16777216 true false 215 106 30 flag false 0 Rectangle -7500403 true true 60 15 75 300 Polygon -7500403 true true 90 150 270 90 90 30 Line -7500403 true 75 135 90 135 Line -7500403 true 75 45 90 45 flower false 0 Polygon -10899396 true false 135 120 165 165 180 210 180 240 150 300 165 300 195 240 195 195 165 135 Circle -7500403 true true 85 132 38 Circle -7500403 true true 130 147 38 Circle -7500403 true true 192 85 38 Circle -7500403 true true 85 40 38 Circle -7500403 true true 177 40 38 Circle -7500403 true true 177 132 38 Circle -7500403 true true 70 85 38 Circle -7500403 true true 130 25 38 Circle -7500403 true true 96 51 108 Circle -16777216 true false 113 68 74 Polygon -10899396 true false 189 233 219 188 249 173 279 188 234 218 Polygon -10899396 true false 180 255 150 210 105 210 75 240 135 240 house false 0 Rectangle -7500403 true true 45 120 255 285 Rectangle -16777216 true false 120 210 180 285 Polygon -7500403 true true 15 120 150 15 285 120 Line -16777216 false 30 120 270 120 leaf false 0 Polygon -7500403 true true 150 210 135 195 120 210 60 210 30 195 60 180 60 165 15 135 30 120 15 105 40 104 45 90 60 90 90 105 105 120 120 120 105 60 120 60 135 30 150 15 165 30 180 60 195 60 180 120 195 120 210 105 240 90 255 90 263 104 285 105 270 120 285 135 240 165 240 180 270 195 240 210 180 210 165 195 Polygon -7500403 true true 135 195 135 240 120 255 105 255 105 285 135 285 165 240 165 195 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 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 0 Rectangle -7500403 true true 151 225 180 285 Rectangle -7500403 true true 47 225 75 285 Rectangle -7500403 true true 15 75 210 225 Circle -7500403 true true 135 75 150 Circle -16777216 true false 165 76 116 square false 0 Rectangle -7500403 true true 30 30 270 270 square 2 false 0 Rectangle -7500403 true true 30 30 270 270 Rectangle -16777216 true false 60 60 240 240 star false 0 Polygon -7500403 true true 151 1 185 108 298 108 207 175 242 282 151 216 59 282 94 175 3 108 116 108 target false 0 Circle -7500403 true true 0 0 300 Circle -16777216 true false 30 30 240 Circle -7500403 true true 60 60 180 Circle -16777216 true false 90 90 120 Circle -7500403 true true 120 120 60 tree false 0 Circle -7500403 true true 118 3 94 Rectangle -6459832 true false 120 195 180 300 Circle -7500403 true true 65 21 108 Circle -7500403 true true 116 41 127 Circle -7500403 true true 45 90 120 Circle -7500403 true true 104 74 152 triangle false 0 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 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 4.1.3 @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ setup go timer count workers mean-wsocialization mean-cscore mean-wscore mean-cknowledge mean-wknowledge num-cupdates num-bupdates equilibrium setup go timer count workers mean-wsocialization mean-cscore mean-wscore mean-cknowledge mean-wknowledge num-cupdates num-bupdates equilibrium setup go timer count workers mean-wsocialization mean-cscore mean-wscore mean-cknowledge mean-wknowledge num-cupdates num-bupdates equilibrium mean-s-wknowledge mean-as-wknowledge setup go timer count workers mean-wsocialization mean-cscore mean-wscore mean-cknowledge mean-wknowledge num-cupdates num-bupdates equilibrium setup go timer count workers mean-wsocialization mean-cscore mean-wscore mean-cknowledge mean-wknowledge num-cupdates num-bupdates equilibrium @#$#@#$#@ @#$#@#$#@ default 0.0 -0.2 0 1.0 0.0 0.0 1 1.0 0.0 0.2 0 1.0 0.0 link direction true 0 Line -7500403 true 150 150 90 180 Line -7500403 true 150 150 210 180 @#$#@#$#@ 0 @#$#@#$#@