globals [ iteration min-energy-for-batna target-price orig-turtles-num max-toughness negotiation-rounds initial-money initial-energy ] turtles-own [ energy money toughness partnered? partner redline offer reached-agreement last-partner-offer var-money-energy-toughness? var-history-agreements-toughness? negotiations-counter agreements-counter high-agreements low-agreements ] ;;;;;;;;;;;;;;;;;;;;;; ;;;Setup Procedures;;; ;;;;;;;;;;;;;;;;;;;;;; to setup ca set max-toughness 10.0 ;; should be the same as the max-toughness in choosers! set iteration 0 set initial-money 50 set initial-energy 50 set min-energy-for-batna energy-loss-per-round set target-price (energy-price-one-buyer * 2) * (1 - discount-two-buyers / 100.0) ;; target price for 2 buyers after discount setup-turtles ;;setup the turtles and distribute them randomly set orig-turtles-num count turtles do-plot end ;;setup the turtles and distribute them randomly to setup-turtles make-turtles ;;create the different turtle types ask turtles [ ifelse toughness = "var-money-energy" [ set var-money-energy-toughness? true set toughness 4.5 ] [ set var-money-energy-toughness? false ] ] ask turtles [ ifelse toughness = "var-history-agreements" [ set var-history-agreements-toughness? true set toughness 4.5 ] [ set var-history-agreements-toughness? false ] ] ask turtles [ if toughness = "discount-dep" [ set toughness (1 - discount-two-buyers / 100) * max-toughness - 0.5 ] ] setup-common-variables ;;sets the variables that all turtles share end ;;create the different turtle types to make-turtles cct initial-num-blue [ set toughness blue-toughness set color blue ] cct initial-num-green [ set toughness green-toughness set color green ] cct initial-num-red [ set toughness red-toughness set color red ] end ;;set the variables that all turtles share to setup-common-variables ask turtles [ init-turtle-common ] ask turtles [setxy random-xcor random-ycor] end to init-turtle-common set money initial-money set energy initial-energy set partnered? false set partner nobody set redline 0 set offer 0 set reached-agreement false set last-partner-offer 0 set negotiations-counter 0 set agreements-counter 0 set high-agreements 0 set low-agreements 0 rt random-float 360 end ;;;;;;;;;;;;;;;;;;;;;;;; ;;;Runtime Procedures;;; ;;;;;;;;;;;;;;;;;;;;;;;; to go without-interruption [ clear-last-round ] ask turtles [ if energy <= 0 [ die ]] ;;turtles with no energy die ask turtles [if energy >= (2 * initial-energy) [hatch 1 [init-turtle-common fd 1] set energy (energy - initial-energy) ] ] ;;turtles with twice the initial-energy multiply set iteration iteration + 1 ask turtles with [ energy > min-energy-for-batna ] [ partner-up ] ;;have turtles try to find a partner with energy > min-energy-for-batna partnered-negotiate let non-partnered-turtles turtles with [ partnered? = false ] ask non-partnered-turtles [ buy-alone-if-needed ] ask turtles [ set money money + money-gain-per-round ] ;;add regular money-gain ask turtles [ set energy energy - energy-loss-per-round ] ;;deduct regular energy loss do-plot end to clear-last-round let partnered-turtles turtles with [ partnered? ] ask partnered-turtles [ set offer 0 set redline 0 set reached-agreement false set last-partner-offer 0 release-partners ] ask turtles [ set label "" ] ask patches with [pcolor != black] [ set pcolor black ] end ;;release partner and turn around to leave to release-partners set partnered? false set partner nobody rt 180 end ;;have turtles try to find a partner ;;This will be done using without-interruption. ;;This is so that other turtles can't act while one is trying to partner up. ;;Also, since other turtles that have already executed partner-up may have ;;caused the turtle executing partner-up to be partnered, ;;a check is needed to make sure the calling turtle isn't partnered. to partner-up ;;turtle procedure without-interruption [ ;;we don't want other turtles acting ifelse(not partnered?) [ ;;make sure still not partnered rt (random-float 90 - random-float 90) fd 1 ;;move around randomly set partner one-of (turtles-at -1 0) with [ not partnered? and energy > min-energy-for-batna ] if partner != nobody [ ;;if successful grabbing a partner, partner up set partnered? true set (partnered?-of partner) true ask partner [ set partner myself ] set heading 270 ;;face partner set (heading-of partner) 90 ] ] [] ;;if partnered, don't do anything ] end ; have partnered turtles negotiate to partnered-negotiate let min-list list ( orig-turtles-num) (count turtles with [ partnered? ]) let negotiating-turtles-num min min-list let partnered-turtles n-of negotiating-turtles-num turtles with [ partnered? ] ;limit number of negotiations in one round to avoid population explosion ask partnered-turtles with [ var-money-energy-toughness? ] [ calculate-var-money-energy-toughenss ] ask partnered-turtles [ set-redline ] set negotiation-rounds (random 10) + 1 ;random num of negotiation rounds to avoid tight coupling between toughness and number of rounds needed for agreement repeat negotiation-rounds [ ask partnered-turtles [ get-partner-last-offer ] ask partnered-turtles [ make-offer ] ask partnered-turtles [ check-for-agreement ] ] ask partnered-turtles [ if reached-agreement [ ask patch-here [ set pcolor pink ] fix-residue make-transaction ] ] ask partnered-turtles with [ var-history-agreements-toughness? ] [ calculate-var-history-agreements-toughenss ] end to set-redline set redline (target-price / 2.0 ) * ( 1 + ( max-toughness - toughness) / max-toughness ) if redline > energy-price-one-buyer [ set redline energy-price-one-buyer ] end to get-partner-last-offer set last-partner-offer offer-of partner end to make-offer if reached-agreement = false [ let min-list list ( ( offer + (redline - offer) / toughness)) money set offer min min-list ] end to check-for-agreement if reached-agreement = false [ if ((offer + offer-of partner) >= target-price) [ set reached-agreement true ] ] end to fix-residue without-interruption [ ;; if offers passed the target price, remove the residue from both offers ;; (first turtle of the pair will do this residue fix for both of them. When the other turtle ;; will do the same check, there will be no residue anymore) let residue (offer + offer-of partner - target-price) set offer (offer - residue / 2.0) set offer-of partner (offer-of partner - residue / 2.0 ) ] end to make-transaction set money (money - offer) set energy (energy + energy-units-in-pack) set label (precision offer 0) end to buy-alone-if-needed if ((energy <= min-energy-for-batna) and (money >= energy-price-one-buyer)) [ set money (money - energy-price-one-buyer) set energy (energy + energy-units-in-pack) set label energy-price-one-buyer ] end ; Calculate toughness for turtles with a toughness of "var-history-agreements" (toughness is set according to the history of previous agreements). ; Aiming to have agreements in which my offer is identical to the partner's offer (not too low in order not to waste money, and not too high so ; that enough agreements will be reached). to calculate-var-history-agreements-toughenss if reached-agreement [ set agreements-counter agreements-counter + 1 if offer > offer-of partner [ set high-agreements high-agreements + 1] if offer < offer-of partner [ set low-agreements low-agreements + 1] ] if agreements-counter >= 18 [ if high-agreements > low-agreements [ if toughness < max-toughness [ set toughness toughness + 0.5 ] ] if high-agreements < low-agreements [ if toughness > 1 [ set toughness toughness - 0.5 ] ] set agreements-counter 0 set high-agreements 0 set low-agreements 0 ] end ; Calculate toughenss for turtles with a toughness of "var-money-energy" (toughness is set according to the amount of money and energy that the turtle has). ; The less money an turtle has, the tougher it is and vice-versa. The less energy an turtle has, the less-tough it is and vice-versa. to calculate-var-money-energy-toughenss let normalized-money ( money * money-gain-per-round ) let normalized-energy (energy / energy-loss-per-round ) set toughness 4.5 if normalized-money > (energy-price-one-buyer * 3) [ set toughness toughness - 1 ] if normalized-money > (energy-price-one-buyer * 5) [ set toughness toughness - 1 ] if normalized-money > (energy-price-one-buyer * 8) [ set toughness toughness - 1 ] if normalized-money < (energy-price-one-buyer * 2) [ set toughness toughness + 1 ] if normalized-money < energy-price-one-buyer [ set toughness toughness + 1 ] if normalized-energy < (2 * initial-energy) * 0.07 [ set toughness toughness - 1 ] if normalized-energy > (2 * initial-energy) * 0.8 [ set toughness toughness + 1 ] end to do-plot set-current-plot "number-of-agents" set-current-plot-pen "blue" let num count turtles with [ color = blue ] if num > 0 [ plot num ] set-current-plot-pen "green" set num count turtles with [ color = green ] if num > 0 [ plot num ] set-current-plot-pen "red" set num count turtles with [ color = red] if num > 0 [ plot num ] set-current-plot "average-money" set-current-plot-pen "blue" let money-list values-from turtles with [ color = blue ] [ money ] if not empty? money-list [ plot mean money-list ] set-current-plot-pen "red" set money-list values-from turtles with [ color = red ] [ money ] if not empty? money-list [ plot mean money-list ] set-current-plot-pen "green" set money-list values-from turtles with [ color = green ] [ money ] if not empty? money-list [ plot mean money-list ] set-current-plot "average-toughness" set-current-plot-pen "blue" let tough-list values-from turtles with [ color = blue ] [ toughness ] if not empty? tough-list [ plot mean tough-list ] set-current-plot-pen "red" set tough-list values-from turtles with [ color = red ] [ toughness ] if not empty? tough-list [ plot mean tough-list ] set-current-plot-pen "green" set tough-list values-from turtles with [ color = green ] [ toughness ] if not empty? tough-list [ plot mean tough-list ] end @#$#@#$#@ GRAPHICS-WINDOW 554 10 984 461 10 10 20.0 1 14 1 1 1 0 1 1 1 -10 10 -10 10 CC-WINDOW 5 498 993 593 Command Center 0 BUTTON 171 16 234 49 setup setup NIL 1 T OBSERVER T NIL BUTTON 276 16 338 49 go go T 1 T OBSERVER T NIL SLIDER 268 77 442 110 money-gain-per-round money-gain-per-round 0 10 1 1 1 NIL SLIDER 268 112 442 145 energy-loss-per-round energy-loss-per-round 0 10 1 1 1 NIL SLIDER 73 94 247 127 energy-price-one-buyer energy-price-one-buyer 1 100 33 1 1 NIL CHOOSER 259 181 397 226 blue-toughness blue-toughness 1 2 3 4 5 6 7 8 9 10 "discount-dep" "var-money-energy" "var-history-agreements" 4 CHOOSER 259 281 397 326 red-toughness red-toughness 1 2 3 4 5 6 7 8 9 10 "discount-dep" "var-money-energy" "var-history-agreements" 2 CHOOSER 259 231 397 276 green-toughness green-toughness 1 2 3 4 5 6 7 8 9 10 "discount-dep" "var-money-energy" "var-history-agreements" 3 SLIDER 84 188 256 221 initial-num-blue initial-num-blue 0 20 15 1 1 NIL SLIDER 84 237 256 270 initial-num-green initial-num-green 0 20 15 1 1 NIL SLIDER 84 285 256 318 initial-num-red initial-num-red 0 20 15 1 1 NIL SLIDER 73 129 247 162 discount-two-buyers discount-two-buyers 10 90 35 1 1 % PLOT 16 343 188 483 number-of-agents time number-of-agents 0.0 10.0 0.0 10.0 true false PENS "blue" 1.0 0 -13345367 true "green" 1.0 0 -10899396 true "red" 1.0 0 -2674135 true PLOT 192 343 362 484 average-money time money 0.0 10.0 0.0 10.0 true false PENS "blue" 1.0 0 -13345367 true "green" 1.0 0 -10899396 true "red" 1.0 0 -2674135 true PLOT 366 343 537 484 average-toughness time toughness 0.0 10.0 0.0 10.0 true false PENS "red" 1.0 0 -2674135 true "blue" 1.0 0 -13345367 true "green" 1.0 0 -10899396 true SLIDER 73 58 247 91 energy-units-in-pack energy-units-in-pack 1 100 22 1 1 NIL @#$#@#$#@ WHAT IS IT? ----------- This model simulates negotiations between 3 types of agents, each with a different "toughness" property. It shows how the toughness affects the outcome of the negotiations in different environments. It also demonstrates dynamic toughness strategies in which the toughness is determined dynamically according to the environment, attempting to yield good results in different environments. HOW IT WORKS ------------ The agents have energy and money. They gain money and lose energy each round. Whenever an agent's energy reaches 0, it dies. Whenever its energy reaches 100, it multiplies. In order to survive, agents need to buy energy packs. An agent can buy one in a certain price, but 2 agents buying together will get a discount. The agents walk around randomly and when they meet another agent they can negotiate on the amount of money each one is willing to pay in order to buy energy together. Only if an agent is about to die, it will buy energy by itself (if it has enough money). The negotiations work as follows: - The number of negotiation rounds is set randomly (1-10). - The 2 sides calculate their red line (maximum price they are willing to pay) according to their toughness. - On each round, each side makes an offer (incrementing the previous offer), also set according to toughness. - If the sum of both offers reaches the required price (after discount), each side pays its offer and gets the energy pack (the meeting location of the 2 agents will then flash and labels with the price paid by each one will be shown). - If the sum of both offers doesn't reach the required price when the negotiation rounds end, the negotiation fails. HOW TO USE IT ------------- Buttons: SETUP: Setup the world according to the sliders explained below. GO: Start the negotiations model. ENERGY-UNITS-IN-PACK: number of energy units in an energy pack. ENERGY-PRICE-ONE-BUYER: price of an energy pack for one buyer. DISCOUNT-TWO-BUYERS: discount given when 2 agents buy 2 energy packs together. MONEY-GAIN-PER-ROUND: how much money is gained each round. ENERGY-LOSS-PER-ROUND: how much energy is lost each round. INITIAL-NUM-BLUE/GREEN/RED: initial number of agents of each type BLUE/GREEN/RED-TOUGHNESS: toughness of each agent type. Tougher agents have a lower red-line and make smaller increments of their offers in each negotiation round. There are constant toughness levels (1-10 where 10 is the toughest) and dynamic toughness levels: DISCOUNT-DEP: toughness determined at setup time according to the amount of discount given. The smaller the discount is, the tougher the agent. VAR-MONEY-ENERGY: toughness is variable, calculated dynamically in each negotiation according to the amount of money and energy the agent has. The less money an agent has, the tougher it is and vice-versa. The less energy an agent has, the less-tough it is and vice-versa. VAR-HISTORY-AGREEMENTS: toughness is variable, calculated periodically according to the history of previous agreements. If an agent paid more on average than his partners in previous agreements -> increase toughness (in order not to waste money). If an agent paid less on average than his partners in previous agreements -> decrease toughness (in order to reach more agreements). Plots: NUMBER-OF-AGENTS: shows the number of agents of each type. AVERAGE-MONEY: shows the average money per agent, for each agent type. AVERAGE-TOUGHNESS: shows the average toughness per agent, for each agent type. THINGS TO NOTICE ---------------- The success of the different agent types can be seen by looking at the number of agents. Notice that in different environment, different toughness levels yield better results. In some environments (for example when the discount is small), it is more important to conserve money, so it is better not reach agreements if that requires paying too much. In other environments (for example when the discount is large), it is more important to reach agreements than to conserve money. Notice that the success of agent types is also determined by the toughness of the other agent types in the world. Notice also how the average money and toughness look like in different scenarios. THINGS TO TRY ------------- Stay with the default values for ENERGY-UNITS-IN-PACK (22), ENERGY-PRICE-ONE-BUYER (33), MONEY-GAIN-PER-ROUND (1), ENERGY-LOSS-PER-ROUND (1). Start with 15 agents per type. Use toughness of 5,4,3 for the different types. Play with the DISCOUNT-TWO-BUYERS slider: run the model with discounts of 35%, 50%, 75%. See which toughness level works better for each discount. Now change one agent type to use one of the dynamic toughness settings. Change the discount and see when the dynamic toughness succeeds. Notice how toughness adapts to the situation and changes. EXTENDING THE MODEL ------------------- Extend the negotiations to include more than 2 agents for an even bigger discount. Allow breaking agreements if a better offer was made by another agent within a certain time period. CREDITS AND REFERENCES ---------------------- Copyright 2007 Zvi Vlodavsky and Doron Zarchy This Negotiation simulation was developed by Zvi Vlodavsky and Doron Zarchy at the Hebrew University, Jerusalem, Israel. The model may be freely used, modified and redistributed provided this copyright is included and it is not used for profit. Portions of this simulation code are based on code from the "PD N-Person Iterated" model by Uri Wilensky. To refer to the "PD N-Person Iterated" model in academic publications, please use: Wilensky, U. (2002). NetLogo PD N-Person Iterated model. http://ccl.northwestern.edu/netlogo/models/PDN-PersonIterated. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. In other publications, please use: Copyright 2002 Uri Wilensky. All rights reserved. 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