Flibs'NFarol
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breed [flibs flib] ;; FLiBs (finite livig blobs) are the agents of the model: they are structured as ;; finite automata. They have "a finite number of states; an input signal ;; causes it to change automatically from one state to another. The kind of automaton ;; used in a flib also generates signals. Incoming and outgoing signals are represented ;; within the automaton by symbols. When a signal is reiceved, the automaton changes ;; state and emits a second signal" (A. K. Dewdney) A flib is considered perfect ;; predictor i.e. very well adapted, when its outgoing signals (prevision/choice) ;; is equal to the next incoming environmental signal. Signals are always binary ;; digits and in this model they are the sum of the signals produced by all flibs. flibs-own [chromosome ;; Every flib owns a chromosome that is a string coding its state transition table; chrom-10 ;; chromosome transposition into decimal number when it is composed by binary digits only ;; (i.e. flibs states are less than three) state ;; the current inner state of the flib choice ;; the binary choice/prevision expressed by the flib regarding go or not to go to the bar fitness ;; a measure of flibs prevision ability to forestall if the bar will be crowded or not ] globals [id ;; a counter to recall flibs one by one bases-replaced ;; counts the number of chromosome bases replacement during generation ;; and hybridization processes attendance ;; counts the number of agents attending the bar tot_attend ;; sum of attendances during one El Farol evening sum_attend ;; summation of all attendances gotten during one El Farol season (i.e. 100 cycles) sigma ;; variance in attendances referred to threshold level sum_sigma ;; summation of all variances gotten during one El Farol season sum_fit_dev ;; summation of flibs fitness standard deviations crowded ;; a switch recording the state of the bar: 1 if overcrowded, 0 if not average ;; mean of flibs population fitness best ;; the best flibs fitness value worst ;; the worst flibs fitness value donor ;; a best performing flib sharing part of its genes recipient ;; a flib acquiring genes from a donor a-split ;; a first cut in the recipient's chromosome b-split ;; a second cut in the recipient's chromosome wild-type ;; a "natural" state chromosome (before mutation) ] ;; ---------- SETUP PROCEDURES ----------------------------------------------------------------------------- ;; ------------------------------------------------------------------------------------------------------------- to setup ;; initializing the model clear-all ;; create the bar area (green) and an elsewhere (blue) ask patches [set pcolor blue] ask patches with [abs pxcor < 10 and abs pycor < 7] [set pcolor green] ask patches with [pxcor = 9 and pycor = 7] [set plabel ["El Farol Bar"]] ask patches with [pxcor = 21 and pycor = -21] [set plabel ["Somewhere else"]] ;; fifty flibs and their chromosomes are generated ask n-of num-flibs patches with [pcolor = blue] [sprout-flibs 1 [ set shape "person" set color white set size 1.8 set chromosome "" set state 0] ;; flibs are initially all out of the bar and their state is conventionally 0 ] ask flibs [chromosome-genesis] if num-states > 2 [notice] reset-ticks end to chromosome-genesis ;; chromosomes are strings randomly built through an iterative procedure: even string's ;; positions are 0 or 1: they represent a possible outgoing signal; odd string's ;; positions represent possible flib's states determined by NUM-STATES slider set chromosome word chromosome (word (random 2) (random num-states)) set bases-replaced bases-replaced + 1 if bases-replaced < num-states * 2 [chromosome-genesis] set bases-replaced 0 end to notice output-print "Chromosomes analysis " output-print "takes place for binary " output-print "string only, " output-print "so analysis is disabled " output-print "when number of flibs " output-print "states are higher than two" end ;; ---------- RUNTIME PROCEDURES --------------------------------------------------------------------------- ;; ------------------------------------------------------------------------------------------------------------- to go ;; every generation one genetic shuffling occurs by default, ;; this frequency can be lowered by slider conjugation-RATE if random-float 1 < mate-rate [conjugation] ;; every season, a mutagenesis process can occur, this frequency can be adjusted by slider MUTATION-RATE ;; the mutational event is preceded by the random choice of a wild-type candidate if random 10000000 / 1000000 < mutation-rate [set wild-type [who] of one-of flibs ask flib wild-type [mutate] ] ;; variables are resetted before another season to El Farol Bar begins ask flibs [set fitness 0 set state 0] set crowded 0 set attendance 0 set tot_attend 0 repeat 100 [el-farol] results-analysis tick end to results-analysis ;; the El Farol seasonal results are summarized and displayed set best max [fitness] of flibs set worst min [fitness] of flibs set average mean [fitness] of flibs ask flibs [set color scale-color red fitness 101 0] set sigma abs (tot_attend / 100 - threshold) set sum_attend sum_attend + tot_attend / 100 set sum_sigma sum_sigma + sigma set sum_fit_dev sum_fit_dev + standard-deviation [fitness] of flibs if num-states < 3 [chrom-analysis] end to chrom-analysis output-print "" output-print "" output-type word "------ season " ticks output-print " ------------" output-print "" ask flibs [set chrom-10 0] binary2decimal output-print "id. bin<-chrom.->dec fitness" end to binary2decimal ask flibs [set chrom-10 chrom-10 + (read-from-string item bases-replaced reverse chromosome) * 2 ^ bases-replaced] set bases-replaced bases-replaced + 1 ifelse bases-replaced < num-states * 4 [binary2decimal] [ set bases-replaced 0 ask flibs [ifelse who <= 9 [output-type word "0"who] [output-type who] output-type word " " chromosome ifelse chrom-10 < 10 [output-type word " " chrom-10] [ifelse chrom-10 < 100 [output-type word " " chrom-10] [output-type word " " chrom-10] ] output-print word " " fitness] ] end ;; Operator 1: A SEASON TO EL FAROL BAR ;; -------------------------------------------------------------------------------------------------------------- to el-farol set id 0 calculations&decisions ;; the attendance is the result of the flibs choices set attendance sum [choice] of flibs / num-flibs set tot_attend tot_attend + attendance ;; comparing the attendance and the threshold value, the (over)crowded state of the bar is determined if attendance >= threshold [set crowded 1 ;; if the bar is crowded, the flibs that have choiced to stay elsewhere are rewarded ask flibs with [choice = 0] [set fitness fitness + 1] ] if attendance < threshold [set crowded 0 ;; if the bar is not crowded, the flibs that have choiced to go there are rewarded ask flibs with [choice = 1] [set fitness fitness + 1] ] end to calculations&decisions ask flib id [ ;; new flibs state is computed set state read-from-string item (4 * state + 2 * crowded + 1) chromosome ;; each flibs prevision is tested and fitness updated set choice read-from-string item (4 * state + 2 * crowded) chromosome ;; flib choice is displayed ifelse choice = 0 [move-to one-of patches with [pcolor = blue]] [move-to one-of patches with [pcolor = green]] ] set id id + 1 if id < num-flibs [calculations&decisions] end ;; Operator 2: GENETIC SHUFFLING ;; -------------------------------------------------------------------------------------------------------------- to conjugation ;; the conjugation process requires two flibs' chromosomes: the donor and the recipient: ;; just the second one undergoes to hybridization select-flibs ask flib recipient [genetic-shuffling] end to select-flibs ;; there are three selection methods to select the "donor" and "recipient" chromosomes: it can be the fittest, ;; the misfittest, or they can be randomly chosen if donor-selection = "random" [set donor [who] of one-of flibs] if donor-selection = "fittest" [set donor [who] of one-of flibs with [fitness = best]] if donor-selection = "misfittest" [set donor [who] of one-of flibs with [fitness = worst]] if recipient-selection = "random" [set recipient [who] of one-of flibs] if recipient-selection = "fittest" [set recipient [who] of one-of flibs with [fitness = best]] if recipient-selection = "misfittest" [set recipient [who] of one-of flibs with [fitness = worst]] ;; self conjugation is forbidden if donor = recipient [select-flibs] end to genetic-shuffling ;; a genes sequence included between a-split and b-split restriction sites is randomly choosen set a-split random (num-states * 4) set b-split random (num-states * 4) set bases-replaced 0 hybridization set fitness 0 end to hybridization ;; the genes' sequence included between a-split and b-split restriction sites on a random ;; flib is replaced by the corresponding sequence on one of the most performing flibs; ;; chromosomes are treated as circular if a-split < b-split [ set chromosome replace-item (a-split + bases-replaced) chromosome (item (a-split + bases-replaced) [chromosome] of flib donor) set bases-replaced (bases-replaced + 1) if bases-replaced < b-split - a-split [hybridization] ] if a-split > b-split [ set chromosome replace-item ((a-split + bases-replaced) mod (num-states * 4)) chromosome (item ((a-split + bases-replaced) mod (num-states * 4)) [chromosome] of flib donor) set bases-replaced (bases-replaced + 1) if bases-replaced < (num-states * 4) - (a-split - b-split) [hybridization] ] set bases-replaced 0 end ;; Operator 3: MUTAGENESIS ;; -------------------------------------------------------------------------------------------------------------- to mutate ;; mutations occur randomly at a given frequency on one locus only let dice random length chromosome let muton read-from-string item dice chromosome ifelse dice mod 2 = 0 [set chromosome replace-item dice chromosome word ((muton + 1) mod 2) ""] [set chromosome replace-item dice chromosome word ((muton + 1) mod num-states) ""] set fitness 0 end ; Copyright 2019 Cosimo Leuci. ; See Info tab for full copyright and license.
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Flibs'NFarol.png | preview | Preview for "Flibs'NFarol" | almost 2 years ago, by Cosimo Leuci | Download |