;;; Global variables globals [ ; Global statistics trade-unit global-cash global-devotion global-tokens ; Global status asks ; list, Listed selling orders. bids ; list, Listed buying orders. latest-volume ; number, Latest average trading price (in $). latest-amount ; number, Latest trading amount (in $) latest-price ; number, Latest average trading price (in $). total-volume ; number, Total trading volume. total-amount ; number, Total trading amount (in $) ; Some cache to improve the computational performance best-bid-price best-ask-price recent-price recent-amount recent-volume recent-change price-to-date ] breed [ orders order ] ; Each order (which is, in our case, always limited) is represented as a turtle. orders-own [ pending? ; boolean, Whether the order is still pending? (and therefore, not matched yet and not visible to other pops) removed? ; Whether the order has been removed? (we intend to reuse the turtle structure for optimization) buy-side? ; boolean, True/Buy, False/Sell price ; number, Price Limit quantity ; number, Size of the order owner ; turtle, Owner Turtle remaining ; number, Remaining quantity of the order ] ; Each behavioral agent is represented as a turtle. ; Trader: represents a party that is capable to trade the token (representing gold, silver, stock, cryptocurrency token, etc). breed [ traders trader ] traders-own [ cash ; number, Cash at hand stockpile ; table (or map) between , Stockpile of the trader my-bid ; order, The bidding order of mine my-ask ; order, The asking order of mine belief ; number, Constant belief of the price ($) utility ; number, Cash + Belief * Stockpile ($) initial-utility ; number, utility value before the trading starts strategy ; number, pre-defined strategy of the trader ] ;;; Backbone of the model ; setup: Initialize the model to setup clear-all reset-ticks create-turtles 1 [ set shape "circle" ] ; Create and populate traders create-traders honest-traders [ set strategy "honest" ] create-traders cunning-traders [ set strategy "cunning" ] ; Both kind of traders receive initial assets under the same rule ask traders [ populate-trader set cash get-random-amount initial-cash set stockpile get-random-amount initial-tokens set belief get-random-amount initial-belief set utility cash + belief * stockpile set initial-utility utility ] arrange-traders ; Calculate the global statistics set global-tokens max list sum [ stockpile ] of traders 1 set global-cash max list sum [ cash ] of traders 1 ; Trade unit is calculated by the trade precision (e.g. precision=0, unit=1; precision=2, unit=0.01) set trade-unit 10 ^ (trade-precision * -1) render-traders end ; go: Loop of the model to go ; Clear previous orders let previous-price latest-price set asks [] set bids [] ; Ask people to trade ask traders [ if strategy = "honest" [ honest-strategy ] if strategy = "cunning" [ cunning-strategy ] set utility cash + belief * stockpile ] matchmake-all calculate-info previous-price ; When there are no referencing prices, use the latest price to help inform traders ifelse length bids > 0 and length asks > 0 [ set best-bid-price [ price ] of item 0 bids set best-ask-price [ price ] of item 0 asks ] [ calculate-best-order latest-price ] ; Finish the tick render-traders tick end ; Calculate some information for the next tick to calculate-info [ previous-price ] ifelse previous-price = 0 [ set recent-change 0 set recent-amount latest-amount set recent-volume latest-volume set recent-price latest-price ] [ ifelse latest-amount > 0 [ set recent-change moving-average recent-change ln (latest-price / previous-price) set recent-amount moving-average recent-amount latest-amount set recent-volume moving-average recent-volume latest-volume set recent-price recent-volume / recent-amount ] [ set recent-change moving-average recent-change 0 ] ] set price-to-date total-volume / total-amount end ; honest-strategy: The "Honest" strategy to honest-strategy if cash >= belief [ submit-order my-bid belief 1 ] if stockpile > 0 [ ; We seek to prevent trading with oneself, and this is the easiest way - just add 0.01 to avoid it submit-order my-ask 0.01 + belief 1 ] end ; honest-strategy: The "Cunning" strategy to cunning-strategy ; Get the best selling price and use it, if it is lower than my belief let purchase-price belief if best-ask-price != 0 and best-ask-price < purchase-price [ set purchase-price best-ask-price ] ; Get the best buying price and use it, if it is higher than my belief let sell-price belief + 0.01 if best-bid-price > sell-price [ set sell-price best-bid-price ] ; Submit the orders if (cash >= purchase-price) [ submit-order my-bid purchase-price 1 ] if (stockpile > 0) [ submit-order my-ask sell-price 1 ] end ;;; Helper: Distribution ; random-amount: Get a random amount of a uniform distribution from [amount/2, amount] to-report get-random-amount [ amount ] report random amount * 0.5 + amount * 0.5 end ; moving-average: Get exponentially weighted moving average. 0 is impossible for price, so we treat it as NULL. to-report moving-average [ existing-value new-value ] let weight 0.1 report existing-value * (1 - weight) + new-value * weight end ;;; Helper: Renderer ; Render all traders. to render-traders if latest-amount = 0 [ stop ] ; Traders ask traders [ set label precision stockpile trade-precision ] ; Market ask turtle 0 [ set size sqrt latest-amount ifelse recent-change > 0 [ set color scale-color red (recent-change / recent-price) 200 0 ] [ set color scale-color green (recent-change / recent-price) -200 0 ] ] end ; Arrange the traders in a circle. to arrange-traders if behaviorspace-run-number != 0 [ stop ] let index 0 let angle 360 / count traders ; We want to keep traders in the same order even when you dynamically introduce new trader. ; With "ask turtles", once new traders get introduced, we would get into trouble. foreach sort-on [who] traders [ the-trader -> ask the-trader [ setxy 0 0 set heading index * angle fd max-pxcor * 0.9 ] set index index + 1 ] end ; The following code is the basis of the matchmake mechanism ;;; Mechanism-related code ; This serves as a constructor which needs to be executed to initialize the trader to populate-trader set my-bid spawn-order true set my-ask spawn-order false set size 2 end ; Spawn an order and return it / turtle-context to-report spawn-order [ s ] let current 0 hatch-orders 1 [ set buy-side? s set pending? false set removed? true set hidden? true set current self set owner myself ] report current end ; We are trying to re-use orders to boost the performance of traders ; s accepts an order; p means price; q means quantity. to submit-order [ s p q ] if p <= 0 [ error "Price cannot go below zero!" ] if q <= 0 [ error "Quantity cannot go below zero!" ] ask s [ set removed? false set pending? true set price p set quantity q set remaining q ] end ; Matchmake all pending? orders ; All pending? orders are randomly sent to the market and get matched ; See the info tab for more details to matchmake-all set latest-amount 0 set latest-volume 0 calculate-best-order 0 let eligible-orders orders with [ removed? = false and pending? = true ] ask eligible-orders [ matchmake ] if latest-amount > 0 [ set latest-price latest-volume / latest-amount ] end ; Matchmake a single pending? order ; If a trader run out of money/stockpile, the orders we touched will be cancelled to matchmake set pending? false ; Deal with the order: if the order is fully fulfilled, we stop and skip the listing process ifelse buy-side? [ ; Remove impossible orders to optimize the performance if price < best-ask-price [ set removed? true stop ] ; Buy order while [ length asks > 0 and [ price ] of first asks < price ] [ execute-order self first asks if removed? = true [ stop ] ] ] [ ; Remove impossible orders to optimize the performance if price > best-bid-price [ set removed? true stop ] ; Sell order while [ length bids > 0 and [ price ] of first bids > price ] [ execute-order first bids self if removed? = true [ stop ] ] ] ; Finish the process and list this offer ; Here, we linearly find the proper position of this offer, and insert it ifelse buy-side? [ let len length bids ifelse len = 0 [ set bids (list self) ] [ let index 0 while [ index < len and [ price ] of (item index bids) > price ] [ set index index + 1 ] set bids insert-item index bids self ] ] [ let len length asks ifelse len = 0 [ set asks (list self) ] [ let index 0 while [ index < len and [ price ] of (item index asks) < price ] [ set index index + 1 ] set asks insert-item index asks self ] ] end ; Calculate "Best" orders (the buying order with the highest price; the selling order with the lowest price) to calculate-best-order [ default ] let best-bid max-one-of orders with [ removed? = false and buy-side? = true ] [ price ] set best-bid-price ifelse-value best-bid = nobody [ default * 0.999 ] [ [ price ] of best-bid ] let best-ask min-one-of orders with [ removed? = false and buy-side? = false ] [ price ] set best-ask-price ifelse-value best-ask = nobody [ default * 1.001 ] [ [ price ] of best-ask ] end ; Order sorter (by price, asc) ; Implicit tiebreaker: time of the order (older orders get prioritized) to-report min-order [ order1 order2 ] if order1 = nobody or [ removed? ] of order1 [ ifelse order2 = nobody or [ removed? ] of order2 [ report nobody ] [ report order2 ] ] if order2 = nobody or [ removed? ] of order2 [ report order1 ] ifelse [ price ] of order1 > [ price ] of order2 [ report order2 ] [ report order1 ] end ; Order sorter (by price, descending) ; Implicit tiebreaker: time of the order (older orders get prioritized) to-report max-order [ order1 order2 ] if order1 = nobody or [ removed? ] of order1 [ ifelse order2 = nobody or [ removed? ] of order2 [ report nobody ] [ report order2 ] ] if order2 = nobody or [ removed? ] of order2 [ report order1 ] ifelse [ price ] of order1 < [ price ] of order2 [ report order2 ] [ report order1 ] end ; Try to execute the two orders to execute-order [ bid-order ask-order ] let bidder [ owner ] of bid-order let asker [ owner ] of ask-order ; For now, the lowest price will be used let deal-price min (list [ price ] of bid-order [ price ] of ask-order) ; Calculate the maximum available let bidder-maximum floor-to-unit ([ [ cash ] of bidder / deal-price ] of bid-order) if bidder-maximum <= 0 [ ask bid-order [ remove-order ] stop ] let asker-maximum [ stockpile ] of asker if asker-maximum <= 0 [ ask ask-order [ remove-order ] stop ] ; Calculate the amount let deal-amount min (list [ remaining ] of bid-order [ remaining ] of ask-order bidder-maximum asker-maximum ) ; Deal! ask bidder [ set cash cash - deal-amount * deal-price set stockpile stockpile + deal-amount ] ask asker [ set cash cash + deal-amount * deal-price set stockpile stockpile - deal-amount ] ; Record it set latest-amount latest-amount + deal-amount set total-amount total-amount + deal-amount set latest-volume latest-volume + deal-amount * deal-price set total-volume total-volume + deal-amount * deal-price ; Change the orders ask (turtle-set bid-order ask-order) [ set remaining remaining - deal-amount check-order ] end ; Check whether a given order is done and needs to be removed to check-order if remaining = 0 [ remove-order ] end ; Forcibly remove an order. to remove-order ifelse buy-side? [ set bids remove self bids ] [ set asks remove self asks ] set pending? false set removed? true end ; Clamp the number between a range. to-report clamp [ min-value source max-value ] ifelse source > max-value [ report max-value ] [ ifelse source < min-value [ report min-value ] [ report source ] ] end ; Floor to individual trade units to-report floor-to-unit [ source ] report floor (source / trade-unit) * trade-unit end ; Copyright 2021 Uri Wilensky. ; See Info tab for full copyright and license. @#$#@#$#@ GRAPHICS-WINDOW 203 10 744 552 -1 -1 13.0 1 13 1 1 1 0 0 0 1 -20 20 -20 20 1 1 1 ticks 30.0 BUTTON 15 11 95 44 NIL setup\n NIL 1 T OBSERVER NIL NIL NIL NIL 1 BUTTON 15 43 95 76 go-once go NIL 1 T OBSERVER NIL NIL NIL NIL 0 BUTTON 100 10 185 75 NIL go T 1 T OBSERVER NIL NIL NIL NIL 0 MONITOR 960 35 1073 80 Price to Date$ price-to-date 2 1 11 MONITOR 760 35 863 80 Latest Price$ latest-price 2 1 11 MONITOR 856 35 961 80 Latest Volume$ latest-volume 2 1 11 MONITOR 1195 35 1284 80 Total Cash$ global-cash 2 1 11 MONITOR 1071 35 1196 80 Circulating Tokens global-tokens 2 1 11 PLOT 760 91 1285 241 Trading Prices Ticks Price 0.0 20.0 5.0 5.0 true true "" "" PENS "Latest" 1.0 0 -13345367 true "" "if ticks > 0 [ plot latest-price ]" TEXTBOX 14 120 164 138 Basic Parameters 12 0.0 1 SLIDER 12 138 184 171 trade-precision trade-precision 0 3 0.0 1 1 NIL HORIZONTAL TEXTBOX 13 187 163 205 Traders & Strategies 12 0.0 1 SLIDER 12 207 184 240 honest-traders honest-traders 0 100 50.0 1 1 NIL HORIZONTAL SLIDER 12 248 184 281 cunning-traders cunning-traders 0 100 50.0 1 1 NIL HORIZONTAL TEXTBOX 760 14 910 32 Market situation 12 0.0 1 TEXTBOX 762 262 912 280 Utility distribution 12 0.0 1 MONITOR 760 284 868 329 Total Utilities sum [ utility ] of traders 0 1 11 MONITOR 867 284 984 329 Average Utilities mean [ utility ] of traders 0 1 11 MONITOR 982 284 1068 329 Avg (Honest) mean [ utility ] of traders with [ strategy = \"honest\" ] 0 1 11 MONITOR 1066 284 1162 329 Avg (Cunning) mean [ utility ] of traders with [ strategy = \"cunning\" ] 0 1 11 MONITOR 1161 284 1286 329 Cunning : Honest % mean [ utility ] of traders with [ strategy = \"cunning\" ] / mean [ utility ] of traders with [ strategy = \"honest\" ] * 100 3 1 11 PLOT 760 339 1287 489 Average Utilities Gain (%) Ticks Utilities 0.0 10.0 0.0 10.0 true true "" "" PENS "Everyone" 1.0 0 -11053225 true "" "if count traders = 0 [ stop ]\nplot mean [ utility / initial-utility * 100 - 100 ] of traders" "Cunning" 1.0 0 -13345367 true "" "if count traders with [ strategy = \"cunning\" ] = 0 [ stop ]\nplot mean [ utility / initial-utility * 100 - 100 ] of traders with [ strategy = \"cunning\" ]" "Honest" 1.0 0 -10899396 true "" "if count traders with [ strategy = \"honest\" ] = 0 [ stop ]\nplot mean [ utility / initial-utility * 100 - 100 ] of traders with [ strategy = \"honest\" ]" SLIDER 12 290 184 323 initial-cash initial-cash 0 2000 1000.0 1 1 $ HORIZONTAL SLIDER 12 332 184 365 initial-tokens initial-tokens 0 200 50.0 1 1 NIL HORIZONTAL SLIDER 11 375 183 408 initial-belief initial-belief 0 100 25.0 1 1 NIL HORIZONTAL @#$#@#$#@ ## WHAT IS IT? This model aims to reproduce phenomena that emerge in modern-day cryptocurrency markets, but is general enough to model any resource traded using the concept of a limited order book. A Limited Order Book is a simple idea: it is a record of outstanding limit orders maintained by a stock exchange. A limit order is a type of order to buy or sell a security at a specific price or better. The simple act of buying and selling in this manner creates complex behaviors at the level of the exchange. ## HOW IT WORKS In this model, each trader holds some `cash`, some tokens (`stockpile`), and trades in the same limited order book. Tokens can be thought of as any tradable good, such as gold, silver, oil, stocks, or cryptocurrency such as Bitcoin or Ethereum. Each trader also holds a firm and constant `belief` in the value of tokens, which is randomly set somewhere in the interval [initial-belief / 2, initial-belief] during the initialization of the model. Time is split into multiple slices and represented as ticks. In each tick, each trader uses a pre-determined strategy to put limited orders on the market. Then, the matchmaking process starts between buyers and sellers. First, we create two empty lists to store pending orders. Then, since we assume that each trader has an equal opportunity of trading, we match each order randomly, during which: 1. If it is a SELL order, we try to find if any of the unmatched BUY orders at the stated sale price or higher. If so, we will execute the order sale at the highest possible price and the two parties will exchange tokens and cash. 2. We repeat this process until there are no remaining matching BUY orders or the selling order is completely executed (this means if you sell 100 tokens, they might not all sell to the same buyer). 2. If the SELL order is not fully executed, we will put it into the unmatched list for selling orders, waiting for other buying orders to pick it up. For BUY orders, we go through the same process but with an opposite bias. In other words, we try to match BUY orders to _cheaper_ prices. Consequently, the market price of the token, as well as the other information available in the market, is calculated and provided to traders in the next tick. In this fairly simplified model, we only implement two simple trading strategies. The first one is called "honest", in which the trader will always try to buy and sell tokens at a price according to his/her belief of the value of that token. The second strategy we call "cunning" and is slightly more complicated. Here, the trader will always buy with a price of either the best-selling-price or their belief (whichever is smaller) and sell with a price of either the best-buying-price or their belief (whichever is larger). Note that after the matchmaking process, both strategies will cancel unfulfilled orders and issue new ones rather than keeping the orders on the exchange. ## HOW TO USE IT ### Basic Usage * SETUP button resets the model. * GO button allows the model to continuously simulate the market. * GO-ONCE button asks the model to simulate the market for 1 tick. ### Parameters The following parameters affect how the market works in this model. * The TRADE-PRECISION slider sets the maximum precision for the number of tokens for each trade. For example, if you set it to 0, the minimum trade unit would be 10^0 = 1. If you set it to 1, the minimum trade unit would be 10^(-1) = 0.1. Default is 1. This models the fact that these currencies are often sold in very small units. * The HONEST-TRADERS slider determines how many traders with the "honest" strategy will be spawned during the setup process. * The CUNNING-TRADERS slider determines how many traders with the "cunning" strategy will be spawned during the setup process. The below parameters all set the maximum amount of CASH, TOKENS, and BELIEF for each agent. Each is initialized according to a random draw from a uniform distribution on the interval [amount/2, amount]: * The INITIAL-CASH slider sets the maximum cash each trader will receive when the model is initialized. * The INITIAL-TOKENS slider sets the maximum tokens each trader will receive when the model is initialized. * The INITIAL-BELIEF slider determines the maximum initial BELIEF of each trader. ### Plots and Monitors The plots and monitors give you a set of tools to measure the market as it transacts. * The **Trading Prices** plot allows you to watch the daily trading prices. * The **Average Utilities Gain** plot allows you to follow the _average utility gain_ of traders with different strategies. Utility, in this model, is defined as the sum of cash and value of the stockpile (cash + belief * stockpile). ## THINGS TO NOTICE * Notice that trading seems to stop only a few hundred ticks into running the model. Why might that be the case? How might you make trading continue longer without changing the code of the model? * Notice that the sum of each traders' utilities is increasing, no matter how many honest or cunning traders are spawned. Why might this happen? Does everyone in the market equally share the gains? Why or why not? ## THINGS TO TRY * **Make all traders honest or cunning.** How fast do traders stop trading in each of these situations? * **Try to mix honest traders with cunning ones.** What happened to the utility gains relative to each other. Why does that occur? * **Try first giving traders lots of CASH. Then trying giving traders lots of TOKENS.** How does the market behave differently across these two scenarios? ## EXTENDING THE MODEL Try to create a more complicated trading strategy (there are a ton of possibilities)! * You could try to allow traders to trade more than 1 unit of TOKENS each trade. * You could also try to allow traders to change their belief in the value of the token according to some random factors or through watching the market dynamics. ## NETLOGO FEATURES While in many NetLogo models we want to ask turtles to do things in a random order to not introduce bias toward particular turtles, here we use `foreach sort-on [who] traders` so that the traders are deterministically called by their `who` property and always rendered in the same order.This feature enables you to dynamically introduce traders into the model and keep its visualization stable and intact. ## RELATED MODELS See the Bidding Market, simple economy, and Sugarscape models to explore more market or economy-related models. ## REFERENCES 1. Baker, J. and Wilensky, U. (2017). NetLogo Bidding Market model. http://ccl.northwestern.edu/netlogo/models/BiddingMarket. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. 2. Chen, J. (2021). Cryptocurrency Trading Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. ## HOW TO CITE If you mention this model or the NetLogo software in a publication, we ask that you include the citations below. For the model itself: * Chen, J. and Wilensky, U. (2021). NetLogo Limited Order Book model. http://ccl.northwestern.edu/netlogo/models/LimitedOrderBook. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. Please cite the NetLogo software as: * Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. This model was developed as part of the Spring 2021 Multi-agent Modeling course offered by Dr. Uri Wilensky at Northwestern University. For more info, visit http://ccl.northwestern.edu/courses/mam/. Special thanks to Teaching Assistants Jacob Kelter, Leif Rasmussen, and Connor Bain. ## COPYRIGHT AND LICENSE Copyright 2021 Uri Wilensky. ![CC BY-NC-SA 3.0](http://ccl.northwestern.edu/images/creativecommons/byncsa.png) This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA. Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu. @#$#@#$#@ 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 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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 30 285 30 240 15 195 45 210 Circle -1 true true 3 83 150 Rectangle -1 true true 65 221 80 296 Polygon -1 true true 195 285 210 285 210 240 240 210 195 210 Polygon -7500403 true false 276 85 285 105 302 99 294 83 Polygon -7500403 true false 219 85 210 105 193 99 201 83 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 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 6.4.0 @#$#@#$#@ setup repeat 35 [ go ] @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ @#$#@#$#@ 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 @#$#@#$#@ 1 @#$#@#$#@