HyperMu’NmGA
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;; _______________________________________________________________________________________________________________ ;; ;; -------------------- HyperMu'NmGA --------------------------------------------------------- HyperMu'NmGA ;; HyperMu'NmGA --------------------------------------------------------- HyperMu'NmGA --------------------- ;; _______________________________________________________________________________________________________________ globals [best_result ;; the numerical value of the chromosome closer to the solution worst_result ;; the numerical value of the chromosome more distant from the solution eureka-time ;; the ticks elapsed to find the optimal solution eureka! ;; binary variable turning on when the optimal solution has just reached reduction-time;; the ticks required to get a 30% reduction of the mutator genes values average donor ;; the turtle having the best chromosome recipient ;; a random turtle different from the donor chromcopy ;; the copy of the chromosome carried by the donor turtle mutcopy ;; the copy of the mutaror gene carried by the donor turtle mate_swcopy ;; the copy of the mate_switch gene carried by the donor turtle mutator_swcopy;; the copy of the mutator_switch gene carried by the donor turtle max-mut.av ;; the highest mutators average value recorded before the problem solution min-mut.av ;; the lowest mutators average value recorded before the problem solution a-split ;; the position of one extreme in a donor's chromosome fragment b-split ;; the position of the second extreme a in a donor's chromosome fragment counter ;; a counter usefull in different blocks ] turtles-own [chromosome ;; a string of digits representing a candidate solution to the problem mutator ;; a gene able to impact positively or negatively on the genetic stability of the ;; chromosome and of itself; its strength is quantified by a whole number mutator_switch;; a gene able to determine the mutation mode; mate_switch ;; a gene able to determine the reproduction mode; ;; it harbours a binary variable: 0 for asexual reproduction, 1 for sexual reproduction fitness ;; the numerical value of the chromosomal strings (if string-value fitness-function mode) ;; or the Hamming distance complement (i.e. the proximity) to the best chromosomal ;; string (if hamming fitness-function mode) ] ;; ---------- SETUP PROCEDURES ------------------------------------------------------------------------------- ;; --------------------------------------------------------------------------------------------------------------- to setup ;; reset parameters and create a number of turtles set by the user clear-all set counter 0 reset-ticks create-turtles turtles-number [ set shape "circle 2" set size 2.3 fd random 15 genotype/fenotype-construction ] message0 set eureka-time 0 end to genotype/fenotype-construction ;; the genotype (chromosome) and the corresponding phenotype (fitness) of the turtle are initially equal to the ;; first answer that is usually given by children to the problem: "what is the greatest number of n digits?" set fitness 10 ^ (genes-number - 1) ;; the initial formal fitness value is converted into a string: it will be the chromosome structure set chromosome word fitness "" set label chromosome ;; chromosome is displayed as label ;; in the "hamming" mode, the fitness function is replaced by the complement of the Hamming distance ;; (i.e. the "Hamming proximity") to the optimal solution if fitness-function = "hamming" [compute-fitness] set mutator 1 set max-mut.av 1 set min-mut.av 1 ;; defining mate_switch gene if reproduction = "asexual" [set mate_switch 0] if reproduction = "sexual" [set mate_switch 1] if reproduction = "sex/asex" [set mate_switch random 2] ;; defining mutator_switch gene if mutate_by = "simple mutagenesis" [set mutator_switch -1] if mutate_by = "additive mutator" [set mutator_switch 0] if mutate_by = "multiplicative mutator" [set mutator_switch 1] if mutate_by = "both mutators" [set mutator_switch random 2] end ;; ---------- RUNTIME PROCEDURES ----------------------------------------------------------------------------- ;; --------------------------------------------------------------------------------------------------------------- to search ask turtles [move] ;; thew worse and the best fitness value are detected set worst_result min [fitness] of turtles set best_result max [fitness] of turtles ;; a message is sent to output when the optimal solution is reached (the solutions are differently detected ;; depending on the chosen fitness function) if eureka-time = 0 and (best_result = 10 ^ genes-number - 1 or best_result = genes-number) [ set eureka-time ticks set eureka! 1 message1 if mutate_by = "simple mutagenesis" [stop] ] ;; max-mut.av and min-mut.av are recorded before the optimal solution is reached if eureka-time = 0 [ if max-mut.av < mean [mutator] of turtles [set max-mut.av mean [mutator] of turtles] if min-mut.av > mean [mutator] of turtles [set min-mut.av mean [mutator] of turtles] ] ;; other STOP conditions if eureka-time > 0 [set reduction-time ticks - eureka-time] if eureka-time > 0 and mean [mutator] of turtles < 0.7 [message2 stop] if eureka-time = 0 and ticks >= 750000 and max [mutator] of turtles < 1 [message3 stop] if eureka-time > 0 and min [mutator] of turtles >= 1.5 and reduction-time > 500000 [message4 stop] ;; two alternative kinds of selective reproduction are admitted: sexual and asexual ;; they take place if the diversity between all chromosomes is not null clear-links if best_result != worst_result [ set donor [who] of one-of turtles with [fitness = best_result] set chromcopy [chromosome] of turtle donor set mutcopy [mutator] of turtle donor set mate_swcopy [mate_switch] of turtle donor set mutator_swcopy [mutator_switch] of turtle donor set recipient [who] of one-of turtles with [fitness != best_result] ask turtle donor [ create-link-to turtle recipient if mate_switch = 0 [cloning] if mate_switch = 1 [recombination] ] ] ;; mutations occur randomly, the frequency is related to the basic mutation-rate (the mutagenicity ;; of the environment) and the total gene number of turtles population if random-float 1 < basic_mutation-rate * turtles-number * (genes-number + 3) [ask one-of turtles [mutation] ] tick set eureka! 0 end ;; TALK TO ME! --------------------------------------------------------------------------------------------------- to message0 output-print "*** HyperMu'NmGA ***" output-print " " end to message1 output-print " OPTIMAL SOLUTION" output-print " reached on " output-print word " tick: " eureka-time end to message2 output-print " " output-print " Mutators mean went" output-print " down 30% under the" output-print " starting value after" output-type " ticks: " output-type reduction-time end to message3 output-print " " output-print " Low evolutive" output-print " potential" end to message4 output-print " " output-print " No mutator < 1.5" output-print " possible endless" output-print " hypermutation status" end ;; GOOD VIBRATIONS ----------------------------------------------------------------------------------------------- to-report patches-ahead [rad dis] ; reports to turtles a set of patches ahead report [patches in-radius rad] of patch-ahead dis end to move ifelse (any? other turtles-on patches-ahead 1 1) [ bk 1 lt random-float 360] [fd 0.001] end ;; Operator 1. FITNESS FUNCTIONS ;; ---------------------------------------------------------------------------------------------------------------- to compute-fitness set fitness 0 set counter 0 if fitness-function = "hamming" [hamming-proximity] if fitness-function = "string-value" [ set fitness read-from-string chromosome] set label chromosome end to hamming-proximity if counter = length chromosome [set counter 0 stop] if item counter chromosome = "9" [ set fitness fitness + 1 ] set counter counter + 1 hamming-proximity end ;; Operator 2. REPRODUCTION ;; ---------------------------------------------------------------------------------------------------------------- to cloning ask turtle recipient [ set chromosome chromcopy set mutator mutcopy set mutator_switch mutator_swcopy set mate_switch mate_swcopy compute-fitness ] end to recombination ;; homologous recombination occurs between the chromosome of a randomly chosen turtle (recipient) and the ;; chromosome of (one of) the most performing one (donor) that offers a code's fragment of its chromosome ;; to the first turtle; the two involved turtles will be highlighted by a link set counter 0 set a-split random genes-number set b-split random genes-number ask turtle recipient [ hybridization compute-fitness] end to hybridization ;; the two selected chromosomal strings give place to hybridization according to a mechanism ;; similar to the crossing-over following to bacterial conjugation; strings are looped, ;; as occur usually in bacterial chromosomes or plasmids ifelse a-split < b-split [set chromosome replace-item (a-split + counter) chromosome (item (a-split + counter) chromcopy) set counter (counter + 1) if counter < b-split - a-split [hybridization]] [if b-split < a-split [set chromosome replace-item ((a-split + counter) mod genes-number) chromosome (item ((a-split + counter) mod genes-number) chromcopy) set counter (counter + 1) if counter < genes-number - a-split + b-split [hybridization]] ] ;; if required, the three donor's regulative genes are transferred into the recipient turtle if reproduction = "sex/asex" [set mate_switch 1] if mutate_by != "simple mutagenesis" [ if random-float 1 < hym-ratio [set mutator mutcopy] if mutate_by = "both mutators" [if random-float 1 < 0.5 [ set mutator_switch mutator_swcopy] ] ] end ;; Operator 3: MUTAGENESIS ;; ---------------------------------------------------------------------------------------------------------------- to mutation ;; simple mutagenesis doesn't involve mutator genes ifelse mutate_by = "simple mutagenesis" [point-mutation compute-fitness if reproduction = "sex/asex" [ ;; mutation of the reproduction mode if random-float 1 < 0.5 [set mate_switch ((mate_switch + 1) mod 2)] ] ] ;; hypermutation can produce a mutation of a structural gene as well as a mutation on the mutator gene; ;; the last one determines the mutation number along the chromosome: it can be 0, 1 or more (multimutation) [if random-float 1 > hym-ratio [multimutation compute-fitness] if random-float 1 < hym-ratio [hypermutation] ;; when the population is reproductively heterogeneous, also the mate_switch gene can mutate if reproduction = "sex/asex" [ if random-float 1 * mutator * mu-expressivity > hym-ratio [ set mate_switch ((mate_switch + 1) mod 2)] ;; mutation of the reproduction mode ] ;; when the population is mutationally heterogeneous, also the mutator_switch gene can mutate if mutate_by = "both mutators" [ if random-float 1 * mutator * mu-expressivity > hym-ratio [ set mutator_switch ((mutator_switch + 1) mod 2)] ;; mutation of the mutator mode ] ] end to point-mutation ;; point-mutations hit randomly only one gene set chromosome replace-item random genes-number chromosome word random 10 "" end to multimutation ;; the multimutations imply different point-mutations in a unique mutation event ;; the number of contemporary point-mutations is determined by the variable stored in the mutator-gene ifelse mutator < genes-number * 4 [repeat mutator [point-mutation]] ;; if the mutator value is too high (more than four times the number of the chromosome genes) in order to avoid ;; overflow events, the number of point-mutations is cut to four times the number of chromosome genes [repeat genes-number * 4 [point-mutation] ] end to hypermutation ;; mutator gene can mutate itself in two alternative ways (additive or multiplicative, decided by ;; mutator_switch gene), the self-mutation effect can be modulated also by the mutator-expressivity parameter set mutator mutator + (random 3 - 1) * mutator ^ mutator_switch * mu-expressivity end
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Attached files
File | Type | Description | Last updated | |
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HyperMu’NmGA.png | preview | HyperMu-Reflection | about 4 years ago, by Cosimo Leuci | Download |
READ_ME.txt | data | attachment | about 1 year ago, by Cosimo Leuci | Download |
Parent: Minimal Genetic Algorithm
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