# PD iterated bdd memory hatch

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## WHAT IS IT?

This model is a multiplayer version of the iterated prisoner's dilemma. It is intended to explore the strategic implications that emerge when the world consists entirely of prisoner's dilemma like interactions. If you are unfamiliar with the basic concepts of the prisoner's dilemma or the iterated prisoner's dilemma, please refer to the PD BASIC and PD TWO PERSON ITERATED models found in the PRISONER'S DILEMMA suite.

## HOW IT WORKS

The PD TWO PERSON ITERATED model demonstrates an interesting concept: When interacting with someone over time in a prisoner's dilemma scenario, it is possible to tune your strategy to do well with theirs. Each possible strategy has unique strengths and weaknesses that appear through the course of the game. For instance, always defect does best of any against the random strategy, but poorly against itself. Tit-for-tat does poorly with the random strategy, but well with itself.

This makes it difficult to determine a single "best" strategy. One such approach to doing this is to create a world with multiple agents playing a variety of strategies in repeated prisoner's dilemma situations. This model does just that. The turtles with different strategies wander around randomly until they find another turtle to play with. If a turtle's scor rises above rep-score, the turtle reproduces: another turtle is created with that strategy. This results in a loss of 10 points for the reproducing turtle. If a turtle's score falls below death-score, it dies. (Note that in this version each turtle remembers their past interactions, but not whom they played against. This is an anonymous version of N-person PD.)

Payoffs

When two turtles interact, they display their respective payoffs as labels.

Each turtle's payoff for each round will determined as follows:

```
| Partner's Action
Turtle's |
Action | C D
------------|-----------------
C | 3 �
------------|-----------------
D | � 1
------------|-----------------
(C = Cooperate, D = Defect)
```

(Note: This way of determining payoff is the opposite of how it was done in the PD BASIC model. In PD BASIC, you were awarded something bad- jail time. In this model, something good is awarded- money.)

## HOW TO USE IT

Buttons:

SETUP: Setup the world to begin playing the multi-person iterated prisoner's dilemma. The number of turtles and their strategies are determined by the slider values.

GO: Have the turtles walk around the world and interact.

GO ONCE: Same as GO except the turtles only take one step.

Sliders:

N-WINNER: When the population with any particular strategy reaches this number, that strategy is declared the winner.

RESCALE-AFTER: Whenever the total population reaches this number, rescale the population to this number by killing of random agents, maintaining the ratio of each strategy in the population.

N-STRATEGY: Multiple sliders exist with the prefix N- then a strategy name (e.g., n-cooperate). Each of these determines how many turtles will be created that use the STRATEGY. Strategy descriptions are found below:

Strategies:

Turtles have bounded memory, and they remember only their last 500 interactions.

RANDOM - randomly cooperate or defect

COOPERATE - always cooperate

DEFECT - always defect

TIT-FOR-TAT - If an opponent cooperates on this interaction cooperate on the next interaction with them. If an opponent defects on this interaction, defect on the next interaction with them. Initially cooperate.

UNFORGIVING - Cooperate until an opponent defects once, then always defect in each interaction with them.

SNEAKY - Defect if an opponent cooperates; if an opponent defects while SNEAKY cooperates, then defect; if an opponent defects while SNEAKY defects, then cooperate.

NOTSOGRIM (trigger) - Cooperate unless partner and I defected last time we met. If last time partner defected and I cooperated, defect with probability 5/7.

UNFORGIVING2 - Cooperate until an opponent defects twice, then always defect in each interaction with them.

ANTI-TIT-FOR-TAT - If an opponent cooperates on this interaction defect on the next interaction with them. If an opponent defects on this interaction, cooperate on the next interaction with them. Initially cooperate.

ANTI-TIT-FOR-TAT-H - If an opponent cooperates on this interaction defect on the next interaction with them. If an opponent defects on this interaction, cooperate on the next interaction with them. Initially defect.

Plots:

TYPE COUNTS - The number of turtles with each strategy.

## THINGS TO NOTICE

Set all the number of player for each strategy to be equal in distribution. For which strategy does the average-payoff seem to be highest? Do you think this strategy is always the best to use or will there be situations where other strategy will yield a higher average-payoff?

Set the number of n-cooperate to be high, n-defects to be equivalent to that of n-cooperate, and all other players to be 0. Which strategy will yield the higher average-payoff?

Set the number of n-tit-for-tat to be high, n-defects to be equivalent to that of n-tit-for-tat, and all other playerst to be 0. Which strategy will yield the higher average-payoff? What do you notice about the average-payoff for tit-for-tat players and defect players as the iterations increase? Why do you suppose this change occurs?

Set the number n-tit-for-tat to be equal to the number of n-cooperate. Set all other players to be 0. Which strategy will yield the higher average-payoff? Why do you suppose that one strategy will lead to higher or equal payoff?

## THINGS TO TRY

Observe the results of running the model with a variety of populations and population sizes. For example, can you get cooperate's average payoff to be higher than defect's? Can you get Tit-for-Tat's average payoff higher than cooperate's? What do these experiments suggest about an optimal strategy?

Currently the UNKNOWN strategy defaults to TIT-FOR-TAT. Modify the UNKOWN and UNKNOWN-HISTORY-UPDATE procedures to execute a strategy of your own creation. Test it in a variety of populations. Analyze its strengths and weaknesses. Keep trying to improve it.

Relate your observations from this model to real life events. Where might you find yourself in a similar situation? How might the knowledge obtained from the model influence your actions in such a situation? Why?

## EXTENDING THE MODEL

Relative payoff table - Create a table which displays the average payoff of each strategy when interacting with each of the other strategies.

Complex strategies using lists of lists - The strategies defined here are relatively simple, some would even say naive. Create a strategy that uses the PARTNER-HISTORY variable to store a list of history information pertaining to past interactions with each turtle.

Evolution - Create a version of this model that rewards successful strategies by allowing them to reproduce and punishes unsuccessful strategies by allowing them to die off.

Noise - Add noise that changes the action perceived from a partner with some probability, causing misperception.

Spatial Relations - Allow turtles to choose not to interact with a partner. Allow turtles to choose to stay with a partner.

Environmental resources - include an environmental (patch) resource and incorporate it into the interactions.

## NETLOGO FEATURES

Note the use of the TO-REPORT primitive in the function CALC-SCORE to return a number

Note the use of lists and turtle ID's to keep a running history of interactions in the PARTNER-HISTORY turtle variable.

Note how agent sets that will be used repeatedly are stored when created and reused to increase speed.

## RELATED MODELS

PD Basic

PD Two Person Iterated

PD Basic Evolutionary

## HOW TO CITE

If you mention this model in an academic publication, we ask that you include these citations for the model itself and for the NetLogo software:

- 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.
- Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

In other publications, please use:

- Copyright 2002 Uri Wilensky. All rights reserved. See http://ccl.northwestern.edu/netlogo/models/PDN-PersonIterated for terms of use.

## COPYRIGHT NOTICE

Copyright 2002 Uri Wilensky. All rights reserved.

Permission to use, modify or redistribute this model is hereby granted, provided that both of the following requirements are followed:

a) this copyright notice is included.

b) this model will not be redistributed for profit without permission from Uri Wilensky. Contact Uri Wilensky for appropriate licenses for redistribution for profit.

This model was created 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.

## Comments and Questions

globals [ ;;number of turtles with each strategy num-random num-cooperate num-defect num-tit-for-tat num-unforgiving num-sneaky num-notsogrim num-unforgiving2 num-anti-tit-for-tat num-anti-tit-for-tat-h ;;number of turtles with each strategy that will reproduce num-random-rep num-cooperate-rep num-defect-rep num-tit-for-tat-rep num-unforgiving-rep num-sneaky-rep num-notsogrim-rep num-unforgiving2-rep num-anti-tit-for-tat-rep num-anti-tit-for-tat-h-rep ;;number of interactions by each strategy num-random-games num-cooperate-games num-defect-games num-tit-for-tat-games num-unforgiving-games num-sneaky-games num-notsogrim-games num-unforgiving2-games num-anti-tit-for-tat-games num-anti-tit-for-tat-h-games ;;total score of all turtles playing each strategy random-score cooperate-score defect-score tit-for-tat-score unforgiving-score sneaky-score notsogrim-score unforgiving2-score anti-tit-for-tat-score anti-tit-for-tat-h-score turtlecount ] turtles-own [ score strategy defect-now? partner-defected? ;;action of the partner i-defected? partnered? ;;am I partnered? partner ;;WHO of my partner (nobody if not partnered) memory-partners memory-partnermove memory-ownmove ] ;;;;;;;;;;;;;;;;;;;;;; ;;;Setup Procedures;;; ;;;;;;;;;;;;;;;;;;;;;; to setup ;; (for this model to work with NetLogo's new plotting features, ;; __clear-all-and-reset-ticks should be replaced with clear-all at ;; the beginning of your setup procedure and reset-ticks at the end ;; of the procedure.) clear-all store-initial-turtle-counts ;;record the number of turtles created for each strategy setup-turtles ;;setup the turtles and distribute them randomly reset-ticks end ;;record the number of turtles created for each strategy ;;The number of turtles of each strategy is used when calculating average payoffs. ;;Slider values might change over time, so we need to record their settings. ;;Counting the turtles would also work, but slows the model. to store-initial-turtle-counts set num-random n-random set num-cooperate n-cooperate set num-defect n-defect set num-tit-for-tat n-tit-for-tat set num-unforgiving n-unforgiving set num-sneaky n-sneaky set num-notsogrim n-not-so-grim set num-unforgiving2 n-unforgiving2 set num-anti-tit-for-tat n-anti-tit-for-tat set num-anti-tit-for-tat-h n-anti-tit-for-tat-h end ;;setup the turtles and distribute them randomly to setup-turtles make-turtles ;;create the appropriate number of turtles playing each strategy setup-common-variables ;;sets the variables that all turtles share end ;;create the appropriate number of turtles playing each strategy to make-turtles crt num-random [ set strategy "random" set color gray - 1 ] crt num-cooperate [ set strategy "cooperate" set color red ] crt num-defect [ set strategy "defect" set color blue ] crt num-tit-for-tat [ set strategy "tit-for-tat" set color lime ] crt num-unforgiving [ set strategy "unforgiving" set color turquoise - 1 ] crt num-sneaky [set strategy "sneaky" set color magenta ] crt num-notsogrim [set strategy "notsogrim" set color yellow] crt num-unforgiving2 [set strategy "unforgiving2" set color 25] crt num-anti-tit-for-tat [set strategy "anti-tit-for-tat" set color 23] crt num-anti-tit-for-tat-h [set strategy "anti-tit-for-tat-h" set color 22] end ;;set the variables that all turtles share to setup-common-variables ask turtles [ set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] setup-memory ;;initialize MEMORY and MEMORY-OWNMOVE list in all turtles end ;;initialize PARTNER-HISTORY list in all turtles to setup-memory let default-memory [] ;;initialize the DEFAULT-HISTORY variable to be a list ;;give each turtle a copy of this list for tracking partner histories ask turtles [ set memory-partners default-memory set memory-partnermove default-memory] ask turtles [ set memory-ownmove default-memory ] end ;;;;;;;;;;;;;;;;;;;;;;;; ;;;Runtime Procedures;;; ;;;;;;;;;;;;;;;;;;;;;;;; to go clear-last-round ask turtles [ partner-up ] ;;have turtles try to find a partner let partnered-turtles turtles with [ partnered? ] ask partnered-turtles [ select-action ] ;;all partnered turtles select action ask partnered-turtles [ play-a-round ] do-bookkeeping ask turtles [ if score > rep-score [ hatch 1 [ set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false ] set score score - 10 ] if score < death-score [die] ] do-counting ;; reproduce-turtles if num-random > n-winner [ output-show "Random wins!" stop] if num-cooperate > n-winner [ output-show "Cooperate wins!" stop] if num-defect > n-winner [ output-show "Defect wins!" stop] if num-tit-for-tat > n-winner [ output-show "Tit-for-tat wins!" stop] if num-unforgiving > n-winner [ output-show "Unforgiving wins!" stop] if num-sneaky > n-winner [ output-show "Sneaky wins!" stop] if num-notsogrim > n-winner [ output-show "Not-so-grim wins!" stop] if num-unforgiving2 > n-winner [ output-show "Unforgiving2 wins!" stop] if num-anti-tit-for-tat > n-winner [ output-show "Anti-tit-for-tat wins!" stop] if num-anti-tit-for-tat-h > n-winner [ output-show "Anti-tit-for-tat-h wins!" stop] if count turtles > rescale-after [ rescale] tick end to clear-last-round let partnered-turtles turtles with [ partnered? ] ask partnered-turtles [ release-partners ] end ;;release partner and turn around to leave to release-partners set partnered? false set partner nobody rt 180 set label "" end ;;have turtles try to find a partner ;;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 if (not partnered?) [ ;;make sure still not partnered rt (random-float 90 - random-float 90) fd advance ;;move around randomly set partner one-of (turtles-at -1 0) with [ not partnered? ] if partner != nobody [ ;;if successful grabbing a partner, partner up set partnered? true set heading 270 ;;face partner ask partner [ set partnered? true set partner myself set heading 90 ] ] ] end ;;choose an action based upon the strategy being played to select-action ;;turtle procedure if strategy = "random" [ act-randomly ] if strategy = "cooperate" [ cooperate ] if strategy = "defect" [ defect ] if strategy = "tit-for-tat" [ tit-for-tat ] if strategy = "unforgiving" [ unforgiving ] if strategy = "sneaky" [ sneaky ] if strategy = "notsogrim" [ notsogrim ] if strategy = "unforgiving2" [ unforgiving2] if strategy = "anti-tit-for-tat" [ anti-tit-for-tat] if strategy = "anti-tit-for-tat-h" [ anti-tit-for-tat-h] end to play-a-round ;;turtle procedure get-payoff ;;calculate the payoff for this round ;;update-history ;;store the results for next time end ;;calculate the payoff for this round and ;;display a label with that payoff. to get-payoff set partner-defected? [defect-now?] of partner set i-defected? defect-now? set memory-partnermove (fput partner-defected? memory-partnermove) if length memory-partnermove > 500 [set memory-partnermove (remove-item 500 memory-partnermove)] set memory-partners (fput [who] of partner memory-partners) if length memory-partners > 500 [set memory-partners (remove-item 500 memory-partners)] set memory-ownmove (fput i-defected? memory-ownmove) if length memory-ownmove > 500 [set memory-ownmove (remove-item 500 memory-ownmove)] ifelse partner-defected? [ ifelse defect-now? [ set score (score + 0) set label 0 ] [ set score (score + beta) set label beta ] ] [ ifelse defect-now? [ set score (score + mu) set label mu ] [ set score (score + 5) set label 5 ] ] end to reproduce-turtles crt num-random-rep [ set strategy "random" set color gray - 1 set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-cooperate-rep [ set strategy "cooperate" set color red set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-defect-rep [ set strategy "defect" set color blue set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-tit-for-tat-rep [ set strategy "tit-for-tat" set color lime set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-unforgiving-rep [ set strategy "unforgiving" set color turquoise - 1 set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-sneaky-rep [ set strategy "sneaky" set color magenta set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-notsogrim-rep [ set strategy "notsogrim" set color yellow set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-anti-tit-for-tat-rep [ set strategy "anti-tit-for-tat" set color 23 set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-anti-tit-for-tat-h-rep [ set strategy "anti-tit-for-tat-h" set color 22 set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] crt num-unforgiving2-rep [ set strategy "unforgiving2" set color 25 set memory-partners [] set memory-partnermove [] set memory-ownmove [] set score 0 set partnered? false set partner nobody set partner-defected? false set i-defected? false setxy random-xcor random-ycor ] ask turtles with [score > rep-score] [set score score - 10] ask turtles with [score < death-score] [die] end ;;;;;;;;;;;;;;;; ;;;Strategies;;; ;;;;;;;;;;;;;;;; ;;All the strategies are described in the Information Tab. to act-randomly set num-random-games num-random-games + 1 ifelse (random-float 1.0 < 0.5) [ set defect-now? false ] [ set defect-now? true ] end to cooperate set num-cooperate-games num-cooperate-games + 1 set defect-now? false end to defect set num-defect-games num-defect-games + 1 set defect-now? true end to tit-for-tat set num-tit-for-tat-games num-tit-for-tat-games + 1 ifelse member? [who] of partner memory-partners [ set partner-defected? item (position [who] of partner memory-partners) memory-partnermove ifelse (partner-defected?) [ set defect-now? true ] [ set defect-now? false ]] [set defect-now? false] end to anti-tit-for-tat set num-anti-tit-for-tat-games num-anti-tit-for-tat-games + 1 ifelse member? [who] of partner memory-partners [ set partner-defected? item (position [who] of partner memory-partners) memory-partnermove ifelse (partner-defected?) [ set defect-now? false ] [ set defect-now? true ]] [set defect-now? false] end to anti-tit-for-tat-h set num-anti-tit-for-tat-h-games num-anti-tit-for-tat-h-games + 1 ifelse member? [who] of partner memory-partners [ set partner-defected? item (position [who] of partner memory-partners) memory-partnermove ifelse (partner-defected?) [ set defect-now? false ] [ set defect-now? true ]] [set defect-now? true] end to unforgiving set num-unforgiving-games num-unforgiving-games + 1 let past-moves filter [ ?1 -> item position ?1 memory-partnermove memory-partners = [who] of partner ] memory-partnermove ifelse member? true past-moves [ set defect-now? true] [set defect-now? false] end to sneaky set num-sneaky-games num-sneaky-games + 1 ifelse member? [who] of partner memory-partners [ set partner-defected? item (position [who] of partner memory-partners) memory-partnermove set i-defected? item (position [who] of partner memory-partners) memory-ownmove ifelse (partner-defected?) [ ifelse (i-defected?) [ set defect-now? false ][ set defect-now? true ] ] [ set defect-now? true ]] [set defect-now? true] end to notsogrim set num-notsogrim-games num-notsogrim-games + 1 ifelse member? [who] of partner memory-partners [ set partner-defected? item (position [who] of partner memory-partners) memory-partnermove set i-defected? item (position [who] of partner memory-partners) memory-ownmove ifelse (partner-defected?) [ ifelse (i-defected?) [ set defect-now? true ][ let w random-float 70 ifelse w < 50 [ set defect-now? true] [set defect-now? false] ] ] [ set defect-now? false ]] [set defect-now? false] end to unforgiving2 set num-unforgiving2-games num-unforgiving2-games + 1 let past-moves filter [ ?1 -> item position ?1 memory-partnermove memory-partners = [who] of partner ] memory-partnermove ifelse length filter [ ?1 -> ?1 = true ] past-moves > 1 [ set defect-now? true] [set defect-now? false] end to rescale do-scoring set turtlecount (count turtles) ask n-of (num-random - (rescale-after * ((num-random) / turtlecount) )) turtles with [ strategy = "random" ] [ die ] ask n-of (num-cooperate - (rescale-after * ((num-cooperate) / turtlecount) )) turtles with [ strategy = "cooperate" ] [ die ] ask n-of (num-defect - (rescale-after * ((num-defect) / turtlecount) )) turtles with [ strategy = "defect" ] [ die ] ask n-of (num-tit-for-tat - (rescale-after * ((num-tit-for-tat) / turtlecount) )) turtles with [ strategy = "tit-for-tat" ] [ die ] ask n-of (num-unforgiving - (rescale-after * ((num-unforgiving) / turtlecount) )) turtles with [ strategy = "unforgiving" ] [ die ] ask n-of (num-sneaky - (rescale-after * ((num-sneaky) / turtlecount) )) turtles with [ strategy = "sneaky" ] [ die ] ask n-of (num-notsogrim - (rescale-after * ((num-notsogrim) / turtlecount) )) turtles with [ strategy = "notsogrim" ] [ die ] ask n-of (num-unforgiving2 - (rescale-after * ((num-unforgiving2) / turtlecount) )) turtles with [ strategy = "unforgiving2" ] [ die ] ask n-of (num-anti-tit-for-tat - (rescale-after * ((num-anti-tit-for-tat) / turtlecount) )) turtles with [ strategy = "anti-tit-for-tat" ] [ die ] ask n-of (num-anti-tit-for-tat-h - (rescale-after * ((num-anti-tit-for-tat-h) / turtlecount) )) turtles with [ strategy = "anti-tit-for-tat-h" ] [ die ] end ;;;;;;;;;;;;;;;;;;;;;;;;; ;;;Plotting Procedures;;; ;;;;;;;;;;;;;;;;;;;;;;;;; ;;procedure called by go that calculates scores and plots to do-bookkeeping do-scoring do-counting do-plotting end ;;calculate the total scores of each strategy to do-scoring set random-score (calc-score "random" num-random) set cooperate-score (calc-score "cooperate" num-cooperate) set defect-score (calc-score "defect" num-defect) set tit-for-tat-score (calc-score "tit-for-tat" num-tit-for-tat) set unforgiving-score (calc-score "unforgiving" num-unforgiving) set sneaky-score (calc-score "sneaky" num-sneaky) set anti-tit-for-tat-score (calc-score "anti-tit-for-tat" num-anti-tit-for-tat) set anti-tit-for-tat-h-score (calc-score "anti-tit-for-tat-h" num-anti-tit-for-tat-h) set num-random-rep count turtles with [(strategy = "random") and (score > rep-score)] set num-cooperate-rep count turtles with [(strategy = "cooperate") and (score > rep-score)] set num-defect-rep count turtles with [(strategy = "defect") and (score > rep-score)] set num-tit-for-tat-rep count turtles with [(strategy = "tit-for-tat") and (score > rep-score)] set num-unforgiving-rep count turtles with [(strategy = "unforgiving") and (score > rep-score)] set num-sneaky-rep count turtles with [(strategy = "sneaky") and (score > rep-score)] set num-notsogrim-rep count turtles with [(strategy = "notsogrim") and (score > rep-score)] set num-unforgiving2-rep count turtles with [(strategy = "unforgiving2") and (score > rep-score)] set num-anti-tit-for-tat-rep count turtles with [(strategy = "anti-tit-for-tat") and (score > rep-score)] set num-anti-tit-for-tat-h-rep count turtles with [(strategy = "anti-tit-for-tat-h") and (score > rep-score)] end ;; returns the total score for a strategy if any turtles exist that are playing it to-report calc-score [strategy-type num-with-strategy] ifelse num-with-strategy > 0 [ report (sum [ score ] of (turtles with [ strategy = strategy-type ])) ] [ report 0 ] end to do-counting set num-random count turtles with [strategy = "random"] set num-cooperate count turtles with [strategy = "cooperate"] set num-defect count turtles with [strategy = "defect"] set num-tit-for-tat count turtles with [strategy = "tit-for-tat"] set num-unforgiving count turtles with [strategy = "unforgiving"] set num-sneaky count turtles with [strategy = "sneaky"] set num-notsogrim count turtles with [strategy = "notsogrim"] set num-unforgiving2 count turtles with [strategy = "unforgiving2"] set num-anti-tit-for-tat count turtles with [strategy = "anti-tit-for-tat"] set num-anti-tit-for-tat-h count turtles with [strategy = "anti-tit-for-tat-h"] end ;;if a strategy has had any interactions, plot the average score per interaction to do-plotting ;; plot stacked histogram of link types set-current-plot "Type counts" let total 0 set-current-plot-pen "random" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "random"] plot-pen-down plotxy ticks total set-current-plot-pen "defect" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "defect"] plot-pen-down plotxy ticks total set-current-plot-pen "cooperate" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "cooperate"] plot-pen-down plotxy ticks total set-current-plot-pen "tit-for-tat" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "tit-for-tat"] plot-pen-down plotxy ticks total set-current-plot-pen "unforgiving" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "unforgiving"] plot-pen-down plotxy ticks total set-current-plot-pen "sneaky" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "sneaky"] plot-pen-down plotxy ticks total set-current-plot-pen "notsogrim" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "notsogrim"] plot-pen-down plotxy ticks total set-current-plot-pen "unforgiving2" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "unforgiving2"] plot-pen-down plotxy ticks total set-current-plot-pen "anti-tit-for-tat" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "anti-tit-for-tat"] plot-pen-down plotxy ticks total set-current-plot-pen "anti-tit-for-tat-h" plot-pen-up plotxy ticks total set total total + count turtles with [strategy = "anti-tit-for-tat-h"] plot-pen-down plotxy ticks total end ; Copyright 2002 Uri Wilensky. All rights reserved. ; The full copyright notice is in the Information tab.

There is only one version of this model, created 4 months ago by Adam Galambos.

## Attached files

File | Type | Description | Last updated | |
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PD iterated bdd memory hatch.png | preview | Preview for 'PD iterated bdd memory hatch' | 4 months ago, by Adam Galambos | Download |

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