patches-own [ chemical ;; amount of chemical on this patch food ;; amount of food on this patch (0, 1, or 2) nest? ;; true on nest patches, false elsewhere nest-scent ;; number that is higher closer to the nest food-source-number ;; number (1, 2, or 3) to identify the food sources ] globals [ final-ticks-food1 final-ticks-food2 final-ticks-food3 gpopulation gdiffusion-rate gevaporation-rate ] ;;;;;;;;;;;;;;;;;;;;;;;; ;;; Setup procedures ;;; ;;;;;;;;;;;;;;;;;;;;;;;; to initialize-globals set gpopulation population set gdiffusion-rate diffusion-rate set gevaporation-rate evaporation-rate end to setup clear-all initialize-globals setup-ants end to setup-ants set-default-shape turtles "bug" crt gpopulation [ set size 2 ;; easier to see set color red ] ;; red = not carrying food setup-patches reset-ticks end to setup-patches ask patches [ setup-nest setup-food recolor-patch ] end to-report go-stop? ifelse (count-food > 0)[ report true ][ report false ] end to compute-fitness if ((sum [food] of patches with [food-source-number = 1] = 0) and (final-ticks-food1 = 0)) [ set final-ticks-food1 ticks ] if ((sum [food] of patches with [food-source-number = 2] = 0) and (final-ticks-food2 = 0)) [ set final-ticks-food2 ticks ] if ((sum [food] of patches with [food-source-number = 3] = 0) and (final-ticks-food3 = 0)) [ set final-ticks-food3 ticks ] end to run-to-grid setup-ants while [go-stop? = true ] [go ] end to-report count-food report sum [food] of patches end to setup-nest ;; patch procedure ;; set nest? variable to true inside the nest, false elsewhere set nest? (distancexy 0 0) < 5 ;; spread a nest-scent over the whole world -- stronger near the nest set nest-scent 200 - distancexy 0 0 end to setup-food ;; patch procedure ;; setup food source one on the right if (distancexy (0.6 * max-pxcor) 0) < 5 [ set food-source-number 1 ] ;; setup food source two on the lower-left if (distancexy (-0.6 * max-pxcor) (-0.6 * max-pycor)) < 5 [ set food-source-number 2 ] ;; setup food source three on the upper-left if (distancexy (-0.8 * max-pxcor) (0.8 * max-pycor)) < 5 [ set food-source-number 3 ] ;; set "food" at sources to either 1 or 2, randomly if food-source-number > 0 [ set food one-of [1 2] ] end to recolor-patch ;; patch procedure ;; give color to nest and food sources ifelse nest? [ set pcolor violet ] [ ifelse food > 0 [ if food-source-number = 1 [ set pcolor cyan ] if food-source-number = 2 [ set pcolor sky ] if food-source-number = 3 [ set pcolor blue ] ] ;; scale color to show chemical concentration [ set pcolor scale-color green chemical 0.1 5 ] ] end ;;;;;;;;;;;;;;;;;;;;; ;;; Go procedures ;;; ;;;;;;;;;;;;;;;;;;;;; to go ;; forever button ask turtles [ if who >= ticks [ stop ] ;; delay initial departure ifelse color = red [ look-for-food ] ;; not carrying food? look for it [ return-to-nest ] ;; carrying food? take it back to nest wiggle fd 1 ] diffuse chemical (gdiffusion-rate / 100) ask patches [ set chemical chemical * (100 - gevaporation-rate) / 100 ;; slowly evaporate chemical recolor-patch ] compute-fitness tick end to return-to-nest ;; turtle procedure ifelse nest? [ ;; drop food and head out again set color red rt 180 ] [ set chemical chemical + 60 ;; drop some chemical uphill-nest-scent ] ;; head toward the greatest value of nest-scent end to look-for-food ;; turtle procedure if food > 0 [ set color orange + 1 ;; pick up food set food food - 1 ;; and reduce the food source rt 180 ;; and turn around stop ] ;; go in the direction where the chemical smell is strongest if (chemical >= 0.05) and (chemical < 2) [ uphill-chemical ] end ;; sniff left and right, and go where the strongest smell is to uphill-chemical ;; turtle procedure let scent-ahead chemical-scent-at-angle 0 let scent-right chemical-scent-at-angle 45 let scent-left chemical-scent-at-angle -45 if (scent-right > scent-ahead) or (scent-left > scent-ahead) [ ifelse scent-right > scent-left [ rt 45 ] [ lt 45 ] ] end ;; sniff left and right, and go where the strongest smell is to uphill-nest-scent ;; turtle procedure let scent-ahead nest-scent-at-angle 0 let scent-right nest-scent-at-angle 45 let scent-left nest-scent-at-angle -45 if (scent-right > scent-ahead) or (scent-left > scent-ahead) [ ifelse scent-right > scent-left [ rt 45 ] [ lt 45 ] ] end to wiggle ;; turtle procedure rt random 40 lt random 40 if not can-move? 1 [ rt 180 ] end to-report nest-scent-at-angle [angle] let p patch-right-and-ahead angle 1 if p = nobody [ report 0 ] report [nest-scent] of p end to-report chemical-scent-at-angle [angle] let p patch-right-and-ahead angle 1 if p = nobody [ report 0 ] report [chemical] of p end ; Copyright 1997 Uri Wilensky. ; See Info tab for full copyright and license. @#$#@#$#@ GRAPHICS-WINDOW 257 10 764 538 35 35 7.0 1 10 1 1 1 0 0 0 1 -35 35 -35 35 1 1 1 ticks 30.0 BUTTON 46 71 126 104 NIL setup NIL 1 T OBSERVER NIL NIL NIL NIL 1 SLIDER 31 106 221 139 diffusion-rate diffusion-rate 0.0 99.0 21 1.0 1 NIL HORIZONTAL SLIDER 31 141 221 174 evaporation-rate evaporation-rate 0.0 99.0 9 1.0 1 NIL HORIZONTAL BUTTON 136 71 211 104 NIL go T 1 T OBSERVER NIL NIL NIL NIL 1 SLIDER 31 36 221 69 population population 0.0 200.0 125 1.0 1 NIL HORIZONTAL PLOT 5 197 248 476 Food in each pile time food 0.0 50.0 0.0 120.0 true false "" "" PENS "food-in-pile1" 1.0 0 -11221820 true "" "plotxy ticks sum [food] of patches with [pcolor = cyan]" "food-in-pile2" 1.0 0 -13791810 true "" "plotxy ticks sum [food] of patches with [pcolor = sky]" "food-in-pile3" 1.0 0 -13345367 true "" "plotxy ticks sum [food] of patches with [pcolor = blue]" MONITOR 7 485 89 530 NIL count-food 17 1 11 MONITOR 806 198 923 243 NIL final-ticks-food1 17 1 11 MONITOR 807 253 924 298 NIL final-ticks-food2 17 1 11 MONITOR 807 307 924 352 NIL final-ticks-food3 17 1 11 @#$#@#$#@ ## WHAT IS IT? In this project, a colony of ants forages for food. Though each ant follows a set of simple rules, the colony as a whole acts in a sophisticated way. ## HOW IT WORKS When an ant finds a piece of food, it carries the food back to the nest, dropping a chemical as it moves. When other ants "sniff" the chemical, they follow the chemical toward the food. As more ants carry food to the nest, they reinforce the chemical trail. ## HOW TO USE IT Click the SETUP button to set up the ant nest (in violet, at center) and three piles of food. Click the GO button to start the simulation. The chemical is shown in a green-to-white gradient. The EVAPORATION-RATE slider controls the evaporation rate of the chemical. The DIFFUSION-RATE slider controls the diffusion rate of the chemical. If you want to change the number of ants, move the POPULATION slider before pressing SETUP. ## THINGS TO NOTICE The ant colony generally exploits the food source in order, starting with the food closest to the nest, and finishing with the food most distant from the nest. It is more difficult for the ants to form a stable trail to the more distant food, since the chemical trail has more time to evaporate and diffuse before being reinforced. Once the colony finishes collecting the closest food, the chemical trail to that food naturally disappears, freeing up ants to help collect the other food sources. The more distant food sources require a larger "critical number" of ants to form a stable trail. The consumption of the food is shown in a plot. The line colors in the plot match the colors of the food piles. ## EXTENDING THE MODEL Try different placements for the food sources. What happens if two food sources are equidistant from the nest? When that happens in the real world, ant colonies typically exploit one source then the other (not at the same time). In this project, the ants use a "trick" to find their way back to the nest: they follow the "nest scent." Real ants use a variety of different approaches to find their way back to the nest. Try to implement some alternative strategies. The ants only respond to chemical levels between 0.05 and 2. The lower limit is used so the ants aren't infinitely sensitive. Try removing the upper limit. What happens? Why? In the `uphill-chemical` procedure, the ant "follows the gradient" of the chemical. That is, it "sniffs" in three directions, then turns in the direction where the chemical is strongest. You might want to try variants of the `uphill-chemical` procedure, changing the number and placement of "ant sniffs." ## NETLOGO FEATURES The built-in `diffuse` primitive lets us diffuse the chemical easily without complicated code. The primitive `patch-right-and-ahead` is used to make the ants smell in different directions without actually turning. ## HOW TO CITE If you mention this model in a publication, we ask that you include these citations for the model itself and for the NetLogo software: * Wilensky, U. (1997). NetLogo Ants model. http://ccl.northwestern.edu/netlogo/models/Ants. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL. * Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL. ## COPYRIGHT AND LICENSE Copyright 1997 Uri Wilensky. ![CC BY-NC-SA 3.0](http://i.creativecommons.org/l/by-nc-sa/3.0/88x31.png) This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit http://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. This model was created as part of the project: CONNECTED MATHEMATICS: MAKING SENSE OF COMPLEX PHENOMENA THROUGH BUILDING OBJECT-BASED PARALLEL MODELS (OBPML). The project gratefully acknowledges the support of the National Science Foundation (Applications of Advanced Technologies Program) -- grant numbers RED #9552950 and REC #9632612. This model was developed at the MIT Media Lab using CM StarLogo. See Resnick, M. (1994) "Turtles, Termites and Traffic Jams: Explorations in Massively Parallel Microworlds." Cambridge, MA: MIT Press. Adapted to StarLogoT, 1997, as part of the Connected Mathematics Project. This model was converted to NetLogo as part of the projects: PARTICIPATORY SIMULATIONS: NETWORK-BASED DESIGN FOR SYSTEMS LEARNING IN CLASSROOMS and/or INTEGRATED SIMULATION AND MODELING ENVIRONMENT. The project gratefully acknowledges the support of the National Science Foundation (REPP & ROLE programs) -- grant numbers REC #9814682 and REC-0126227. 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