pcgp with node sorting

cfg/gym.yaml

@@ -13,6 +13,7 @@ columns: 100
 recur: 0.2
 out_m_rate: 0.3
 env: 'HopperBulletEnv-v0'
+i_start: -0.5
 functions:
   - f_add
   - f_subtract

src/crossover.jl

@@ -8,7 +8,7 @@ export single_point_crossover,
 
 "single point crossover, genes from p1 up to a random point, then genes from p2"
 function single_point_crossover(cfg::NamedTuple, c1::CGPInd, c2::CGPInd)
-    cpoint = c1.n_in + c1.n_out + 3 * rand(2:(min(length(c1.nodes)-c1.n_in,
+    cpoint = c1.n_in + c1.n_out + 4 * rand(2:(min(length(c1.nodes)-c1.n_in,
                                                  length(c2.nodes)-c2.n_in)-2))
     if rand(Bool)
         ngenes = deepcopy([c1.chromosome[1:cpoint]; c2.chromosome[(cpoint+1):end]])
@@ -41,8 +41,8 @@ end
 "take random nodes from each parent equally, up to the size of the smaller parent"
 function random_node_crossover(cfg::NamedTuple, c1::CGPInd, c2::CGPInd)
     l = min(length(c1.chromosome), length(c2.chromosome)) - max(c1.n_out, c2.n_out)
-    p = rand(Bool, Int64(round(l / 3)))
-    p_nodes = repeat(p, inner=3)
+    p = rand(Bool, Int64(round(l / 4)))
+    p_nodes = repeat(p, inner=4)
     append!(p_nodes, rand(Bool, c1.n_out))
     genes = rand(length(c1.chromosome))
     genes[p_nodes] = c1.chromosome[p_nodes]
@@ -114,7 +114,7 @@ function node_crossover(cfg::NamedTuple, c1::CGPInd, c2::CGPInd,
             if i in c2_nodes
                 append!(genes, get_genes(c2, i))
             else
-                append!(genes, rand(3))
+                append!(genes, rand(4))
             end
         end
     end

src/individual.jl

@@ -77,26 +77,32 @@ function CGPInd(cfg::NamedTuple, chromosome::Array{Float64}, genes::Array{Int16}
     CGPInd(cfg.n_in, cfg.n_out, chromosome, genes, outputs, nodes, buffer, fitness)
 end
 
+snap(x) = map(x->argmin(abs.(p .- x)), fc)
+
 function CGPInd(cfg::NamedTuple, chromosome::Array{Float64})::CGPInd
     R = cfg.rows
     C = cfg.columns
     # chromosome: node genes, output genes
-    genes = reshape(chromosome[1:(R*C*3)], R, C, 3)
-    # TODO: recurrency is ugly and slow
-    maxs = collect(1:R:R*C)
-    maxs = round.((R*C .- maxs) .* cfg.recur .+ maxs)
-    maxs = min.(R*C + cfg.n_in, maxs .+ cfg.n_in)
-    maxs = repeat(maxs, 1, R)'
-    genes[:, :, 1] .*= maxs
-    genes[:, :, 2] .*= maxs
-    genes[:, :, 3] .*= length(cfg.functions)
-    genes = Int16.(ceil.(genes))
-    outputs = Int16.(ceil.(chromosome[(R*C*3+1):end] .* (R * C + cfg.n_in)))
+    ps = chromosome[cfg.n_out+1:4:end]
+    ps_sort = sortperm(ps)
+    xs = chromosome[cfg.n_out+2:4:end][ps_sort]
+    ys = chromosome[cfg.n_out+3:4:end][ps_sort]
+    fs = chromosome[cfg.n_out+4:4:end][ps_sort]
+    sort!(ps)
+    xgenes = xs .* ((cfg.recur * (1.0 .- ps) .+ ps) .- cfg.i_start ) .+ cfg.i_start
+    ygenes = ys .* ((cfg.recur * (1.0 .- ps) .+ ps) .- cfg.i_start ) .- cfg.i_start
+    positions = collect(LinRange(cfg.i_start, 0.0, cfg.n_in+1))
+    positions = [positions[1:cfg.n_in]; ps]
+    genes = Array{Int16}(undef, R, C, 3)
+    genes[:, :, 1] = Int16.(map(x->argmin(abs.(positions .- x)), xgenes))
+    genes[:, :, 2] = Int16.(map(x->argmin(abs.(positions .- x)), ygenes))
+    genes[:, :, 3] = Int16.(ceil.(fs .* length(cfg.functions)))
+    outputs = Int16.(ceil.(chromosome[(R*C*4+1):end] .* (R * C + cfg.n_in)))
     CGPInd(cfg, chromosome, genes, outputs)
 end
 
 function CGPInd(cfg::NamedTuple)::CGPInd
-    chromosome = rand(cfg.rows * cfg.columns * 3 + cfg.n_out)
+    chromosome = rand(cfg.n_out + cfg.rows * cfg.columns * 4)
     CGPInd(cfg, chromosome)
 end
 
@@ -156,9 +162,9 @@ end
 
 function get_genes(c::CGPInd, node_id::Integer)::Array{Float64}
     if node_id > c.n_in
-        return c.chromosome[(node_id-c.n_in-1)*3 .+ (1:3)]
+        return c.chromosome[(node_id-c.n_in-1)*4 .+ (1:4)]
     else
-        return zeros(3)
+        return zeros(4)
     end
 end
 
@@ -173,8 +179,8 @@ end
 "set the genes of node_id to genes"
 function set_genes!(c::CGPInd, node_id::Integer, genes::Array{Float64})
     if node_id > c.n_in
-        @assert length(genes) == 3
-        c.chromosome[(node_id-c.n_in-1)*3 .+ (1:3)] = genes
+        @assert length(genes) == 4
+        c.chromosome[(node_id-c.n_in-1)*4 .+ (1:4)] = genes
     end
 end
 

test/individual.jl

@@ -6,7 +6,7 @@ import YAML
     cfg = get_config("test.yaml")
     ind = CGPInd(cfg)
 
-    @test length(ind.nodes) == 3 * cfg.columns + cfg.n_in
+    @test length(ind.nodes) == cfg.rows * cfg.columns + cfg.n_in
     for node in ind.nodes
         if node.active
             @test node.x >= 1
@@ -56,7 +56,7 @@ end
     @test all(genes .<= 1.0)
 
     set_genes!(ind2, ind.n_in+1, genes)
-    @test all(ind.chromosome[1:3] .== ind2.chromosome[1:3])
+    @test all(ind.chromosome[1:4] .== ind2.chromosome[1:4])
 
     for i in 1:length(ind.nodes)
         genes = get_genes(ind, i)

test/test.yaml

@@ -14,6 +14,7 @@ recur: 0.0
 n_in: 10
 n_out: 3
 out_m_rate: 0.3
+i_start: -0.5
 functions:
   - f_add
   - f_subtract