Flibs'NFarol

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.