Perceptron

globals [
  epoch-error   ;; average error in this epoch
  perceptron    ;; a single output-node
  input-node-1  ;; keep the input nodes in globals so we can refer
  input-node-2  ;; to them directly and distinctly
]

;; A perceptron is modeled by input-node and bias-node agents
;; connected to an output-node agent.

;; Connections from input nodes to output nodes
;; in a perceptron.
links-own [ weight ]

;; all nodes have an activation 
;; input nodes have a value of 1 or -1
;; bias-nodes are always 1
turtles-own [activation]

breed [ input-nodes input-node ]

;; bias nodes are input-nodes whose activation
;; is always 1.
breed [ bias-nodes bias-node ]

;; output nodes compute the weighted sum of their
;; inputs and then set their activation to 1 if
;; the sum is greater than their threshold.  An
;; output node can also be the input-node for another
;; perceptron.
breed [ output-nodes output-node ]
output-nodes-own [threshold]

;;
;; Setup Procedures
;;

to setup
  clear-all

  ;; set our background to something more viewable than black
  ask patches [ set pcolor white - 3 ]

  set-default-shape input-nodes "circle"
  set-default-shape bias-nodes "bias-node"
  set-default-shape output-nodes "output-node"

  create-output-nodes 1 [
    set activation random-activation
    set xcor 6
    set size 2
    set threshold 0
    set perceptron self
  ]

  create-bias-nodes 1 [
    set activation 1
    setxy 3 7
    set size 1.5
    my-create-link-to perceptron
  ]

  create-input-nodes 1 [
    setup-input-node
    set label "Node 1"
    setxy -6 5
    set input-node-1 self
  ]

  create-input-nodes 1 [
    setup-input-node
    set label "Node 2"
    setxy -6 0
    set input-node-2 self
  ]

  ask perceptron [ compute-activation ]
  reset-ticks
end 

to setup-input-node
    set activation random-activation
    set size 1.5
    my-create-link-to perceptron
    set label-color magenta
end 

;; links an input or bias node to an output node

to my-create-link-to [ anode ] ;; input or bias node procedure
  create-link-to anode [
    set color red + 1
    ;; links start with a random weight
    set weight random-float 0.1 - 0.05
  ]
end 

;;
;; Runtime Procedures
;;

;; train sets the input nodes to a random input
;; it then computes the output
;; it determines the correct answer and back propagates the weight changes

to train ;; observer procedure
  set epoch-error 0
  repeat examples-per-epoch
  [
    ;; set the input nodes randomly
    ask input-nodes
      [ set activation random-activation ]

    ;; distribute error
    ask perceptron [
      compute-activation
      update-weights target-answer
      recolor
    ]
  ]

  ;; plot stats
  set epoch-error epoch-error / examples-per-epoch
  set epoch-error epoch-error * 0.5
  tick
end 

;; compute activation by summing the inputs * weights 
;; and run through sign function which determines whether
;; the computed value is above or below the threshold

to compute-activation ;; output-node procedure
  set activation sign sum [ [activation] of end1 * weight ] of my-in-links
  recolor
end 

to update-weights [ answer ] ;; output-node procedure
  let output-answer activation

  ;; calculate error for output nodes
  let output-error answer - output-answer

  ;; update the epoch-error
  set epoch-error epoch-error + (answer - sign output-answer) ^ 2

  ;; examine input output edges and set their new weight
  ;; increasing or decreasing it by a value determined by the learning-rate
  ask my-in-links [
    set weight weight + learning-rate * output-error * [activation] of end1
  ]
end 

;; computes the sign function given an input value

to-report sign [input]  ;; output-node procedure
  ifelse input > threshold
  [ report 1 ]
  [ report -1 ]
end 

to-report random-activation ;; observer procedure
  ifelse random 2 = 0
  [ report 1 ]
  [ report -1 ]
end 

to-report target-answer ;; observer procedure
  let a [activation] of input-node-1 = 1
  let b [activation] of input-node-2 = 1
  report ifelse-value (run-result (word "my-" target-function " a b")) [1][-1]
end 

to-report my-or [a b];; output-node procedure
  report (a or b)
end 

to-report my-xor [a b] ;; output-node procedure
  report (a xor b)
end 

to-report my-and [a b] ;; output-node procedure
  report (a and b)
end 

to-report my-nor [a b] ;; output-node procedure
  report not (a or b)
end 

to-report my-nand [a b] ;; output-node procedure
  report not (a and b)
end 

;; test runs one instance and computes the output

to test ;; observer procedure
  ask input-node-1 [ set activation test-input-node-1-value ]
  ask input-node-2 [ set activation test-input-node-2-value ]

  ;; compute the correct answer
  let correct-answer target-answer

  ;; color the nodes
  ask perceptron [ compute-activation ]

  ;; compute the answer

  let output-answer [activation] of perceptron

  ;; output the result
  ifelse output-answer = correct-answer
  [
    user-message (word "Output: " output-answer "\\nTarget: " correct-answer "\\nCorrect Answer!")
  ]
  [
    user-message (word "Output: " output-answer "\\nTarget: " correct-answer "\\nIncorrect Answer!")
  ]
end 


;; Sets the color of the perceptron's nodes appropriately
;; based on activation

to recolor ;; output, input, or bias node procedure
  ifelse activation = 1
    [ set color white ]
    [ set color black ]
  ask in-link-neighbors [ recolor ]

  ifelse show-weights?
  [ resize-recolor-links ]
  [
    ask my-in-links [
      set thickness 0
      set label ""
      set color red + 1
    ]
  ]
end 

;; resize and recolor the edges
;; resize to indicate weight
;; recolor to indicate positive or negative

to resize-recolor-links
  ask links [
    set label precision weight 4
    set thickness 0.1 + 4 * abs weight
    ifelse weight > 0
    [ set color red + 1 ]
    [ set color blue ]
  ]
end