;;***************************************************************************
;;                                Variables                                 |
;;***************************************************************************
globals
[
 count-flag        ;; number of agents with flag value 1
 count-flag-list   ;; a list of count-flag throughout the flocking motion
 time              ;; iteration step
]
turtles-own   ;;Variables of the agents
[
 flockmates ;; red agents within its vision-depth and vision angle
 mates      ;; white agents withing its vision and angle
 speed      ;; speed of the agent
 flag       ;; flag value of the agent: either 0 or 1.
]

;;**************************************************************************
;;                                Setup Environment                        |
;;**************************************************************************
to setup
 ca
 cct red-agents [set heading random-float 360
                 set color red
                 setxy random-xcor random-ycor
                 set speed 1.1 + random-float 0.9
                ]
  cct white-agents [set heading random-float 360
                     set color white
                     setxy random-xcor random-ycor
                     set speed 1.1 + random-float 0.9
                   ]
   ask patches [set pcolor gray]
   ask turtles [set flag 0]
   set count-flag-list[]
   set time 0

   if watch-one-of-red-agents?
     [watch one-of turtles with [color = red]]
end

;;***************************************************************************
;;                                  Go                                      |
;;***************************************************************************
to go
 no-display
 set time (time + 1)
 set count-flag 0
 ;;ask turtles [set label flag]
 ask turtles [setup-flockmates-and-mates]
 ask turtles [flock]
 ask turtles [set count-flag (count-flag + flag)]
 set count-flag-list lput count-flag count-flag-list
 ask turtles [jump speed]
 ask turtles [count-flock]
 display
end

to setup-flockmates-and-mates  ;; turtles procedure
 set flockmates (turtles in-cone vision-depth vision-angle) with [self != myself and color = red]
 set mates (turtles in-cone vision angle) with [self != myself and color = white]
end

to flock    ;; turtles procedure
;; it is not a simulation for single species.....so we implement the mulitple agent flocking in a
;; separate procedure
;;  ifelse (heterospecies = 0)
;;    [if any? flockmates
;;      [let nearest-neighbour min-one-of flockmates [distance myself]
;;       ifelse distance nearest-neighbour < min-separation
;;        [change-speed
;;         set flag 0
;;         separate nearest-neighbour]
;;        [ adjust-speed nearest-neighbour
;;          set flag 1
;;          align
;;          cohere ]
;;       ]
;;     ]
    do-mixed-species-flocking
end

to separate [nearest-neighbour]  ;; turtle procedure
 turn-away (heading-of nearest-neighbour) max-separate-turn
end

to align  ;; turtle procedure
 turn-towards average-flockmate-heading max-align-turn
end

to-report average-flockmate-heading  ;; turtle procedure
 let i sum values-from flockmates [sin heading]
 let j sum values-from flockmates [cos heading]
 ifelse (j != 0)
   [report atan sum values-from flockmates [sin heading]
             sum values-from flockmates [cos heading]
   ]
   [report 0]
end

to cohere  ;; turtle procedure
 turn-towards average-heading-towards-flockmates max-cohere-turn
end

to-report average-heading-towards-flockmates
 report atan mean values-from flockmates [sin (towards myself + 180)]
             mean values-from flockmates [cos (towards myself + 180)]
end


to turn-towards [new-heading max-turn]  ;; turtle procedure
 turn-at-most (subtract-headings new-heading heading) max-turn
end

to turn-away [new-heading max-turn]  ;; turtle procedure
 turn-at-most (subtract-headings heading new-heading) max-turn
end

;; turn right by "turn" degrees (or left if "turn" is negative),
;; but never turn more than "max-turn" degrees
to turn-at-most [turn max-turn]  ;; turtle procedure
 ifelse abs turn > max-turn
   [ ifelse turn > 0
       [ rt max-turn ]
       [ lt max-turn ] ]
   [ rt turn ]
end

to adjust-speed [agents]
 ifelse color-of agents = red
   [set speed mean values-from flockmates [speed]]
   [set speed mean values-from mates [speed]]
end

to change-speed
 set speed 1.1 + random-float 0.9
end

to count-flock
;;  ifelse (heterospecies = 0)
;;    [set-current-plot "mean-flock"
;;     plot count-flag
;;    ]
   count-hetero-flock
end

to count-hetero-flock
 set-current-plot "heterospecies-mean-flock"
 plot mean count-flag-list
end

to scatter
 ask turtles [setxy random-xcor random-ycor set heading random-float 360]
end
to do-mixed-species-flocking
 locals [nearby-red-agents nearby-white-agents]
 let x 0
 let y 0
 ;; let probability random-float (heterospecific-attraction + 1)
 ifelse any? flockmates
   [set x 1][set x 0]        ;; x = 1 indicates the presence of red agents in the flock
 ifelse any? mates
   [set y 1] [set y 0]       ;; y = 1 indicates the presence of white agents in the flock

 if x = 1
   [set nearby-red-agents min-one-of flockmates [distance myself]]
 if y = 1
   [set nearby-white-agents min-one-of mates [distance myself]]

 ;; this is the one that needs to be changed
 ifelse color = red
   [ifelse x = 1
     [ifelse y = 0
       [ifelse distance nearby-red-agents > min-separation          ;; x = 1 y = 0
         [set flag 1 mixed-cohere nearby-red-agents mixed-align nearby-red-agents][set flag 0 separate nearby-red-agents]
       ] ;; end of y = 0
       [ifelse distance nearby-red-agents < distance nearby-white-agents   ;;x = 1 y = 1
         [ifelse distance nearby-red-agents > min-separation
           [set flag 1 mixed-cohere nearby-red-agents mixed-align nearby-red-agents] [set flag 0 separate nearby-red-agents]
         ]
         [ifelse distance nearby-white-agents > min-separation and random-float 101 <= (heterospecific-attraction)
           [set flag 1 mixed-cohere nearby-white-agents mixed-align nearby-white-agents] [set flag 0 separate nearby-white-agents]
         ]

       ] ;; end of y = 1
      ]
      [ ;; beginning of x = 0
        ifelse y = 1 and distance nearby-white-agents > min-separation and random-float 101 <= (heterospecific-attraction)
          [set flag 1 mixed-cohere nearby-white-agents mixed-align nearby-white-agents] []
      ]
    ]
    [;; for color = white
     ifelse y = 1
     [ifelse x = 0
       [ifelse distance nearby-white-agents > min-separation          ;; x = 0 y = 1
         [set flag 1 mixed-cohere nearby-white-agents mixed-align nearby-white-agents][set flag 0 separate nearby-white-agents]
       ] ;; end of x = 0
       [ifelse distance nearby-white-agents < distance nearby-red-agents   ;;x = 1 y = 1
         [ifelse distance nearby-white-agents > min-separation
           [set flag 1 mixed-cohere nearby-white-agents mixed-align nearby-white-agents] [set flag 0 separate nearby-white-agents]
         ]
         [ifelse distance nearby-red-agents > min-separation and random-float 101 <= (heterospecific-attraction)
          [set flag 1 mixed-cohere nearby-red-agents mixed-align nearby-red-agents] []
         ]
       ] ;; end of x = 1
      ]
      [ ;; beginning of y = 0
        ifelse x = 1 and distance nearby-red-agents > min-separation and random-float 101 <= (heterospecific-attraction)
          [set flag 1 mixed-cohere nearby-red-agents mixed-align nearby-red-agents] []
      ]
    ]
end

to mixed-cohere [agents] ;; procedure for cohesion for heterogeneous agents
 adjust-speed agents
 let sinheading 0
 let cosheading 0
 let new-heading 0
 ifelse (color-of agents = red)
    [set sinheading mean values-from flockmates [sin (towards myself + 180)]
    set cosheading mean values-from flockmates [cos (towards myself + 180)]
    ifelse (cosheading != 0)
      [set new-heading atan mean values-from flockmates [sin (towards myself + 180)]
                            mean values-from flockmates [cos (towards myself + 180)]
      ]
      [set new-heading 0]
    ]
    [set sinheading mean values-from mates [sin (towards myself + 180)]
     set cosheading mean values-from mates [cos (towards myself + 180)]
      ifelse (cosheading != 0)
        [set new-heading atan mean values-from mates [sin (towards myself + 180)]
                            mean values-from mates [cos (towards myself + 180)]
        ]
        [set new-heading 0]
    ]
    turn-towards new-heading max-cohere-turn
end

to mixed-align [agents] ;; procedure for alignment for heterogeneous agents
 let i 0
 let j 0
 let average-heading 0
 ifelse color-of agents = red
   [set i sum values-from flockmates [sin heading]
    set j sum values-from flockmates [cos heading]
    ifelse (j != 0)
      [set average-heading atan sum values-from flockmates [sin heading]
                                sum values-from flockmates [cos heading]
      ]
      [set average-heading 0]
   ]
   [set i sum values-from mates [sin heading]
    set j sum values-from mates [cos heading]
    ifelse (j != 0)
      [set average-heading atan sum values-from mates [sin heading]
                                sum values-from mates [cos heading]
      ]
      [set average-heading 0]
   ]
   turn-towards average-heading max-align-turn
end


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@#$#@#$#@
HETEROSPECIES FLOCKING
-----------------------
Sifat Momen, Bala Amavasai and Nazmul Siddique
Microsystems and Machine Vision Laboratory,
Materials and Engineering Research Institute,
Sheffield Hallam University, Pond Street, Sheffield S1 1WB, United Kingdom.
E-mail: sifu_008@yahoo.com
Web: https://www.shu.ac.uk/research/meri/mmvl

WHAT IS IT?
-----------
This model is an attempt to mimic the flocking of multiple agent types. The resulting motion also resembles the flocking effect in birds and schools of fish. Agents within each species are homogeneous, i.e. no leader is pre-designated to guide the motion, rather it is the local interaction between the neighbours that sets the motion.

The flocking model was first introduced by Craig Reynolds in 1986 [1]. Three rules typically "separation", "alignment" and "cohesion" is used to make the flocking movement.

The simulation shown here-in is an attempt to extend the flocking model developed by Reynolds. It analyses how the presence of multiple species affects flocking motion.

In this simulation, there are two types of agents: red agents and white agents. Each agent type follows three principle steering behaviours. In addition to it, the heterospecific attraction between the two types of agents govern the interaction between the two agent types.

The model is inspired by mixed species flocking visible in nature. Mixed species flocking is commonly visible in forests where different species of birds are available.
It is hypothesized that mixed species flocking takes place as a means of predator defence. The most popular hypothesis, in fact, is that mixed species flocking improves foraging efficiency. However this is true provided the birds have the same sort of diets and also that the species do not compete over food and in condition where food depletion is not at a risk.

It is envisaged that the model would be of much importance in the area of swarm robotics and agent based systems. Still now, scientists and researchers are using the model of single species flocking in these areas. However we forsee that the model of mixed species flocking would be very valuable as this leads to increasing in flocking efficiency.


HOW IT WORKS
------------
The rules are the same as that of the Reynolds.
However we have introduced an extra parameter called "heterospecific attraction". Heterospecific attraction is the attraction between two different agent types - in this case the attraction between red-agents and white-agents.


HOW TO USE IT
-------------
setup - Use this button to setup the initial position of the agents
go - Use this button to run the simulation
scatter - Use this button to randomly scatter the agents
red-agents - Determines the number of red-agents
vision-angle - Determines the angle of vision of red-agents. For example if                            vision-angle is 60 deg. the red-agent can see 30 deg to its left and 30                 deg to its right
vision-depth - Determines the number of patches the red-agents can see
min-separation - The minimum amount of separation allowed
max-align-turn, max-cohere-turn, max-separate-turn - The maximum angle the agents can                                                        align, cohere and separate
white-agents - The number of white agents
angle - Determines the angle of vision of white agents
vision - Determines the number of patches the white agents can see
heterospecific-attraction - Determines the amount of inter-agent attraction


THINGS TO NOTICE
----------------
Observe how the flocking of the agents vary with the heterospecific-attraction


RELATED MODELS
--------------
Flocking model in the Netlogo model Library


CREDITS AND REFERENCES
----------------------
1. Craig Reynolds https://www.red3d.com/cwr/boids/
2. Flocking model in the netlogo model library

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NetLogo 3.1.1
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