ESL is an actor-based language that is currently in development. Actors are like objects with their own computational thread. As part of development we are keen to stress test the number of actors that can concurrently exist. Schelling’s [Schelling TC (1969) Models of segregation. Am Econ Rev 59:488–493] is a classic model of residential segregation that lends itself to an actor-based application. Residents are either red or blue and like to be co-located with residents of their own colour. If they find themselves in a neighbourhood that is overwhelmed by the opposite colour then they move to a random empty location. Residents can be implemented as actors that independently move around until they feel secure. The video below shows a 400 by 200 grid of ESL actors starting with random allocations and moving towards a stable system:
Here is a snapshot of a 1000 by 600 grid of ESL actors (takes much longer to get to a stable position):
export main;
// Behaviour types:
// Main runs the application.
// Agent exists at a location in the world.
// Grid is an external Java actor for the display.
type Main = Act { Time(Int); }
type Agent = Act { Turn; }
type Grid = Act { SetColour(Int,Int,Str); }
// External functions...
intToFloat::(Int)->Float = builtin[(Int)->Float]('runtime.actors.Builtins','intToFloat',1);
round::(Float)->Int = builtin[(Float)->Int]('runtime.actors.Builtins','round',1);
// Basic list-processing...
occurrences[T](x::T,l::[T])::Int =
case l {
[][T] -> 0;
h::T:t::[T] when h=x -> 1 + occurrences[T](x,t);
h::T:t::[T] -> occurrences[T](x,t);
}
flatten[T](lists::[[T]])::[T] =
case lists {
h::[T];
t::[[T]];
h:t -> h+flatten[T](t);
[][[T]] -> [][T];
}
nth[T](l::[T],n::Int)::T =
case l {
h::T;
t::[T];
h:t -> if n = 0 then h; else nth[T](t,n-1);
[][T] -> throw[T]('cannot take nth element.');
}
replaceNth[T](l::[T],n::Int,x::T)::[T] =
case l {
[][T] -> throw[[T]]('cannot replace nth of []');
h::T:t::[T] when n=0 -> x:t;
h::T:t::[T] -> h:replaceNth[T](t,n-1,x);
}
// Parameters that control the application:
similarpc::Int = 70; // 70% of neighbours should be the same colour.
width::Int = 1000; // Number of locations wide.
height::Int = 600; // Number of locations high.
redpc::Int = 60; // Starting with 60% red population.
emptypc::Int = 10; // 10% of locations hould be empty.
empty::Int = 0; // The encoding for an empty location.
red::Int = 1; // The encoding for a red location.
blue::Int = 2; // The encoding for a bloue location.
limit::Int = 1000000; // A millisecond time limit.
// The locations are represented on a width*height matrix represented as nested lists...
opp(c::Int)::Int = if c = red then blue; else red;
colour(c::Int)::Str = if c = red then 'red'; else if c = empty then 'white'; else 'blue';
legalx(x::Int)::Bool = (x = 0) or (x = width) or ((x > 0) and (x < width));
legaly(y::Int)::Bool = (y = 0) or (y = height) or ((y > 0) and (y < height));
population::[[Int]] =
[ [ probably(100-emptypc)::Int {
probably(redpc)::Int red; else blue;
} else empty
| w::Int <- 0..width ]
| h::Int <- 0..height ];
popEl(x::Int,y::Int)::Int = nth[Int](nth[[Int]](population,y),x);
popElp(x::Int,y::Int)::[Int] = [popEl(x%width,y%height)];
popSet(x::Int,y::Int,c::Int)::Void = {
population := replaceNth[[Int]](population,y,replaceNth[Int](nth[[Int]](population,y),x,c));
grid <- SetColour(x,y,colour(c));
}
popSim(x::Int,y::Int)::Int =
let surround::[Int] = flatten[Int]([ popElp(x0,y0) | x0::Int <- (x-1)..(x+2), y0::Int <- (y-1)..(y+2), ?not((x0 = x) and (y0 = y)) ]);
colour::Int = popEl(x,y);
in let sim::Int = occurrences[Int](colour,surround);
diff::Int = occurrences[Int](opp(colour),surround);
in round((intToFloat(sim)/(intToFloat(sim+diff)))* 100.0);
// An external Java actor that deals with the graphics...
grid::Grid = new 'esl.grid.Grid'[Grid](width,height,1);
act agent(x::Int,y::Int)::Agent {
// An agent lives at (x,y) and wants to live in a neighbourhood
// of agents with a similar colour...
findEmpty(x0::Int,y0::Int)::Void =
if popEl(x0,y0) = empty
then {
popSet(x0,y0,popEl(x,y));
popSet(x,y,empty);
x := x0;
y := y0;
} else findEmpty(random(width),random(height));
Turn -> {
grab(population) {
// If the neighbours are less than the required
// similarity then find an empty location and
// move to it...
if popSim(x,y) < similarpc
then {
findEmpty(random(width),random(height));
} else {}
}
self <- Turn;
}
}
act main::Main {
// Create the agents, send their initial colour to the
// GUI and then send them a Turn message to start the
// simulation
agents::[Agent] = [][Agent];
-> {
for y::Int in 0..height do {
for x::Int in 0..width do {
if popEl(x,y) <> empty
then {
let a::Agent = new agent(x,y);
in {
agents := a:agents;
grid <- SetColour(x,y,colour(popEl(x,y)));
a <- Turn;
}
} else {}
}
}
}
Time(n::Int) when n > limit -> {
print[Str]('STOP ' + n + ' ' + limit);
stopAll();
}
Time(n::Int) -> {}
}
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