globals [continue]

turtles-own [mygoal in-nodes out-nodes current]

patches-own [
  isgoal
  obstacle
]

to setup
  clear-all
  ask patches [
    set isgoal 0
    set obstacle 0
   ;; set potential 0
  ]

  ask patch max-pxcor max-pycor [set-goal]

  create-agents

  ;; set one goal

  reset-ticks
end

to reset
  ask patches [
    ifelse obstacle = 1
    [set-obstacle]
    [ifelse (isgoal = 1)
        [set-goal]
        [set pcolor black]
    ]
  ]
  ask turtles [die]
  create-agents
end


to createGoals
  ask patch 0 5 [set-goal]
  ask patch -4 -8 [set-goal]
  repeat 3 [ask patch random-pxcor random-pycor [set-goal]]
end

to set-obstacle
  set obstacle 1
  if (isgoal = 1)[set isgoal 0]
  set pcolor red
  ;; set potential (- potential-level)
end

to set-goal
  set isgoal 1
  if (obstacle = 1)[set obstacle 0]
   set pcolor yellow
   ;; set potential potential-level
end


to erase-obstacle
  set pcolor black set obstacle 0
  ;; set potential 0
end

to erase-potential
  ask patches [
    ifelse obstacle = 1
    [set-obstacle]
    [ifelse (isgoal = 1)
        [set-goal]
        [set pcolor black
         ;; set potential 0
        ]
    ]
  ]
  ask turtles [die]
end

to create-agents
  let xorg -15
  let yorg -15
  create-turtles number-turtles [
    set color orange
    set size 1.5
    ifelse (number-turtles = 1) [
      setxy xorg yorg
    ][
      setxy random-xcor random-ycor
    ]
    set in-nodes []
    set out-nodes []
    set mygoal min-one-of patches with [isgoal = 1][distance self]
    set current init-current
    if (trace = true) [show (sentence "current node : " current "current goal " mygoal)]
  ]
end

;;------------------------------------
;;
;; search machine
;;
;;------------------------------------

;; get the patch
to-report get-patch [node]
  report first node
end
;; get the value of the node
to-report get-val [node]
  report item 1 node
end

to-report get-cost [node]
  report item 2 node
end

to-report get-parent [node]
  report item 3 node
end

to search
  while [get-patch current != mygoal] [
  search-step
  ]
  print "Success!!"
  draw-path current
end

to search-step
  let new-nodes generate
  set in-nodes merge-nodes new-nodes in-nodes
  if (trace = true) [print (sentence "size in-nodes : " length in-nodes)]
  set in-nodes sort-nodes in-nodes
  if (trace = true) [print (sentence "sorted in-nodes: " length in-nodes ", " in-nodes)]
  let proposed first in-nodes
  if (proposed = [])[
    stop
  ]
  set current proposed
  set in-nodes bf in-nodes
  set out-nodes (fput (get-patch current) out-nodes) ;; we only put patches in the out-nodes list
  if (trace = true) [show (sentence "current node : " current)]
  ask (get-patch current) [if (pcolor != green)[set pcolor blue]]
end

to-report generate
  let aset nobody
   set aset ([neighbors] of (get-patch current)) with [obstacle = 0]
  ifelse (any? aset) [
    ask aset  [if (pcolor = black)[set pcolor white]]
    let lst1 [self] of aset ;; transformer en listes...
                            ;; show (sentence "aset : " lst1)
    set lst1 (remove-nodes lst1 out-nodes) ;; delete nodes which have already been visited
    let result map [ x -> make-node x current ] lst1 ;; make a list of nodes [patch value]
    report result
  ]
  [
    show (sentence "blocked ;-) ")
    report []
  ]
end


;; NOTE: DEPENDS ON THE ALGORITHM
to-report init-current
  ifelse Algorithm = "Dijkstra"
  [report (make-node1 patch-here 0 0 [])]
  [report (make-node1 patch-here distance-to-goal patch-here 0 [])]
end

;; NOTE: DEPENDS ON THE ALGORITHM
to-report make-node [p n]
  let r 0
  ifelse Algorithm = "Dijkstra" [
    set r (list p (1 + (get-val n)) 0 n)
  ][
    let g 1 + get-cost n
    let h distance-to-goal p
    ;; Note: holds the cost and the parent.
    ;; Used by A* algorithm
    set r (make-node1 p h g n)
  ]
  report r
end

to-report make-node1 [p h c n]
  report (list p h c n)
end

to-report cost [node]
  ifelse (Algorithm = "Astar") [
   ;  report (get-val node) + (get-cost node)
     report (get-cost node)
  ][
     report (get-val node)
  ]
end

to-report distance-to-goal [p]
  let r 0
  set r [distance p] of mygoal
 ;; show (sentence "distance from " p " to " goal " = " r)
  report r
end



to-report sort-nodes [lst-nodes]
   ; let lst sort-by [(cost ?1) < (cost ?2)] lst-nodes

   let lst []
  ifelse (Algorithm != "Astar")
    [ set lst sort-by [[x y] -> (get-val x) < (get-val y)] lst-nodes ]
   [ set lst sort-by [[x y] -> (get-val x)+ weight * (cost x) < (get-val y)+ weight * (cost y)] lst-nodes]  ;; take the weight of the cost g (and not only the heuristic h*) into account
   if (lst = []) [
     (show "pas de solution !!" )
    report []
   ]
   report lst
end


;; crée une liste avec le min des couts...
to-report merge-nodes [lst-new lst-ref]
  let res []
  ;set lst-ref sort-by [(cost ?1) < (cost ?2)] lst-ref
  let lst map get-patch lst-ref
  while [lst-new != []] [
    let node (first lst-new)
    let pos position (get-patch node) lst
    ifelse (pos = false)[
      set res (fput node res)
    ][
      let v 0
      let g 0
      let p current
      ifelse ((cost node) < (cost (item pos lst-ref))) [
        set v get-val node
        set g get-cost node
        set p current
      ][
       set v get-val (item pos lst-ref)
        set g get-cost (item pos lst-ref)
        if (Algorithm != "Best-first") [
           set p get-parent (item pos lst-ref)
        ]
      ]
      ;; reconstruct the node
      set res (fput (make-node1 (get-patch node) v g p) res)
      ;; suppress the node from old list
      set lst-ref remove-item pos lst-ref
      set lst map get-patch lst-ref
    ]
    set lst-new (bf lst-new)
  ]
  set res (sentence res lst-ref)
  report res
end

to-report remove-nodes [lst ref-lst]
  let res []
  while [lst != []] [
    if not member? (first lst) ref-lst [
      set res (fput (first lst) res)
    ]
    set lst (bf lst)
  ]
  report res
end

to draw-path [node]
  while [node != []] [
    ask get-patch node [set pcolor green]
    set node get-parent node
  ]
end

;;------------------------------------
;;
;;    Turtles
;;
;;-------------------------------------

to search-turtles
  ask-concurrent turtles [search]
  tick
end

to step-turtles
  ask turtles [search-step]
end


;;----------------------------------------
;;
;;   drawing
;;
;;----------------------------------------

to draw-goals
  if mouse-down?
  [ ask patches
    [ if ((abs (pxcor - mouse-xcor)) < 1) and ((abs (pycor - mouse-ycor)) < 1)
      [ set-goal]]]
  display
end



to draw-obstacles
  if mouse-down?
  [ ask patches
    [ if ((abs (pxcor - mouse-xcor)) < 1) and ((abs (pycor - mouse-ycor)) < 1)
      [ set-obstacle]]]
  display
end

to eraser
  if mouse-down?
  [ ask patches
    [ if ((abs (pxcor - mouse-xcor)) < 1) and ((abs (pycor - mouse-ycor)) < 1)
      [ erase-obstacle]]]
  display
end
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1

SWITCH
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SLIDER
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weight
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HORIZONTAL

@#$#@#$#@
## WHAT IS IT?

A Generic search algorithm for A* (Astar), Dijkstra and 'best first' in a tile world (patch world as used in some games).

## HOW IT WORKS
Use a generic algorithm where only a few variations makes the difference between A*, Dijskstra and best first.

## HOW TO USE IT
Type 'reset' to start a new search without removing obstacles.. Setup clears all
Draw obstacles (and click again to stop the process)
Choose an algorithm (default is A*)
Click on 'search-turtles' to get the whole search or 'step-turtle' to move forward one step at a time

- Red patches are obstacles
- Yellow patches are the goals
- Blue patches are the one that have been visited by the engine
- White patches are generated through the algorithm (neighbors of visited nodes)
- Green patches form the path found by the algorithm

## THINGS TO NOTICE

Notice the difference between those three algorithms. The difference lies in the make-node function, and in the evaluation function.
*Note that the turtle does not move!* Exploration is done via the engine, but not through the behavior of a turtle. This is a "path planning" model and not a "space exploration" one.

## THINGS TO TRY

Draw obstacles and goals as you wish... See how it works step by step...

## CREDITS AND REFERENCES

(C) Jacques Ferber - wwww.lirmm.fr/~ferber   - 2014
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