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Almost completed redesign of the system. Needs tested.

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temporaryWork^2
youainti 5 years ago
parent 90478868e1
commit cf9a581bec
1 changed files with 153 additions and 152 deletions
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297
julia_code/BellmanResidual_Operators.jl
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@ -32,6 +32,9 @@ Three key functions
- Constellation Satellite Stocks Evolution
"""
# ╔═╡ f8779824-9d59-4458-926f-10beb3cd3866
abstract type TransitionRule end
# ╔═╡ 9b1c2f62-ec19-4667-8f93-f8b52750e317
md"""
### Parameterize the physical world
@ -62,22 +65,15 @@ begin
loss_param = 2e-3;
loss_weights = loss_param*(ones(N_constellations,N_constellations) - LinearAlgebra.I);
#orbital decay rate
decay_param = 0.01;
#debris generation parameters
autocatalysis_param = 0.001;
satellite_loss_debris_rate = 5.0;
launch_debris_rate = 0.05;
#Todo, wrap physical model as a struct with the parameters
bm = BasicModel(
loss_param
,loss_weights
,decay_param
,autocatalysis_param
,satellite_loss_debris_rate
,launch_debris_rate
,0.01
,0.001
,5.0
,0.05
)
end
@ -98,37 +94,52 @@ function survival(
end
# ╔═╡ 152f3a3c-a565-41bb-8e59-6ab0d2315ffb
#debris evolution
function H(
stocks::Array{Float32}
,debris::Array{Float32}
,launches::Array{Float32}
, physical_model::BasicModel
)
#get changes in debris from natural dynamics
natural_debris_dynamics = (1-physical_model.decay_rate+physical_model.autocatalysis_rate) * debris
begin
#debris evolution
struct BasicDebrisEvolution <: TransitionRule
physical_model::BasicModel
end
function (self::BasicDebrisEvolution)(
stocks::Array{Float32}
,debris::Array{Float32}
,launches::Array{Float32}
)
#get changes in debris from natural dynamics
natural_debris_dynamics = (1-self.physical_model.decay_rate + self.physical_model.autocatalysis_rate) * debris
#get changes in debris from satellite loss
satellite_loss_debris = physical_model.satellite_collision_debris_ratio * (1 .- survival(stocks,debris,physical_model))'*stocks
#get changes in debris from satellite loss
satellite_loss_debris = self.physical_model.satellite_collision_debris_ratio * (1 .- survival(stocks,debris,self.physical_model))'*stocks
#get changes in debris from launches
launch_debris = physical_model.launch_debris_ratio*sum(launches)
#get changes in debris from launches
launch_debris = self.physical_model.launch_debris_ratio*sum(launches)
#return total debris level
return natural_debris_dynamics .+ satellite_loss_debris .+ launch_debris
#return total debris level
return natural_debris_dynamics .+ satellite_loss_debris .+ launch_debris
end
end
# ╔═╡ 25ac9438-2b1d-4f6b-9ff1-1695e1d52b51
#stock update rules
function G(
stocks::Array{Float32}
,debris::Array{Float32}
,launches::Array{Float32}
, physical_model::BasicModel
)
return LinearAlgebra.diagm(survival(stocks,debris,physical_model) .- physical_model.decay_rate)*stocks + launches
begin
#stock update rules
struct BasicStockEvolution <: TransitionRule
physical_model::BasicModel
end
function (self::BasicStockEvolution)(
stocks::Array{Float32}
,debris::Array{Float32}
,launches::Array{Float32}
)
return LinearAlgebra.diagm(survival(stocks,debris,self.physical_model) .- self.physical_model.decay_rate)*stocks + launches
end
end
# ╔═╡ 6bf01e30-d054-4a98-9e0d-58d7da4e5524
begin
H = BasicDebrisEvolution(bm)
G = BasicStockEvolution(bm)
end;
# ╔═╡ 29ff1777-d276-4e8f-8582-4ca191f2e2ff
md"""
## Setup Neural Networks
@ -178,35 +189,8 @@ function planner_policy_function_generator(number_params=32)
end
# ╔═╡ 95bfc9d8-8427-41d6-9f0f-f155296eef91
#I don't think that these are going to be needed
begin
#= CUSTOM LAYERS
=#
#Custom passthrough layer
passthrough(x::Array{Float32}) = x
# custom split layer
struct Split{T}
paths::T
end
Split(paths...) = Split(paths)
Flux.@functor Split
(self::Split)(x::AbstractArray{Float32}) = tuple(map(f -> f(x), self.paths))
### TESTING ###
#multiple branches
Flux.Parallel(vcat,
passthrough, passthrough, passthrough
)(([1f0],[2f0,3],[4f0]))
end
# ╔═╡ ae6681e0-c796-4145-a313-75f74b4993ad
#add branch generator
# ╔═╡ bbca5143-f314-40ea-a20e-8a043272e362
md"""
@ -214,58 +198,42 @@ md"""
"""
# ╔═╡ 340da189-f443-4376-a82d-7699a21ab7a2
abstract type EconomicParameters end
abstract type EconomicModel end
# ╔═╡ 206ac4cc-5102-4381-ad8a-777b02dc4d5a
begin #basic linear model
struct EconModel1 <: EconomicParameters
struct EconModel1 <: EconomicModel
β::Float32
payoff_array::Array{Float32}
policy_costs::Array{Float32}
end
function payoff1(
s::Vector{Float32}
,d::Vector{Float32}
,a::Vector{Float32}
,em::EconModel1
)
return em.payoff_array*s - em.policy_costs*a
end
function (em::EconModel1)(
s::Vector{Float32}
,d::Vector{Float32}
,a::Vector{Float32}
)
return em.payoff_array*s - em.policy_costs*a
end
end
# ╔═╡ eebb8706-a431-4fd1-b7a5-40f07a63d5cb
begin #basic CES model
struct CESParams <: EconomicParameters
β::Float32
r::Float32 #elasticity of subsititution
payoff_array::Array{Float32}
policy_costs::Array{Float32}
debris_costs::Array{Float32}
end
function CES_with_debris(
struct CESParams <: EconomicModel
β::Float32
r::Float32 #elasticity of subsititution
payoff_array::Array{Float32}
policy_costs::Array{Float32}
debris_costs::Array{Float32}
end
function (em::CESParams)(
s::Vector{Float32}
,d::Vector{Float32}
,a::Vector{Float32}
,em::CESParams
)
)
return (em.payoff_array*(s.^em.r) - em.debris_costs*(d.^em.r)).^(1/em.r) - em.policy_costs*a
end
end
# ╔═╡ f8d582cb-10cf-4c72-8127-787f662e0567
#=
This struct organizes information about a given constellation operator
=#
struct ConstellationOperator
payoff_fn::Function
econ_params::EconomicParameters
value::Flux.Chain
#policy_params::Flux.Params #cutting this for now
end
#TODO: create a function that takes this struct and checks backprop
# ╔═╡ b433a7ec-8264-48d6-8b95-53d2ec4bad05
md"""
### examples of parameter models
@ -317,12 +285,19 @@ md"""
# Loss function specification
"""
# ╔═╡ 9d4a668a-23e3-4f36-86f4-60e242caee3b
begin #testing data
s1 = ones(Float32,N_constellations)
d1 = ones(Float32,N_debris)
end
# ╔═╡ 41271ab4-1ec7-431f-9efb-0f7c3da2d8b4
#Constellation operator loss function
function Ξ(
s::Vector{Float32}
,d::Vector{Float32}
,physical_model::PhysicalParameters
,debris_transition::BasicDebrisEvolution
,stocks_transition::BasicStockEvolution
,co::ConstellationOperator
,policy::Flux.Chain
)
@ -330,8 +305,8 @@ function Ξ(
a = policy((s,d))
#get updated stocks and debris
s′ = G(s,d,a,physical_model)
d′ = H(s,d,a,physical_model)
s′ = stocks_transition(s,d,a)
d′ = debris_transition(s,d,a)
bellman_residuals = co.value((s,d)) - co.payoff_fn(s,d,a,co.econ_params) - co.econ_params.β*co.value((s′,d′))
@ -341,70 +316,96 @@ function Ξ(
return sum(bellman_residuals.^2, maximization_condition)
end
# ╔═╡ 9d4a668a-23e3-4f36-86f4-60e242caee3b
begin #testing data
s1 = ones(Float32,N_constellations)
d1 = ones(Float32,N_debris)
end
# ╔═╡ cd55e232-493d-4849-8bd7-b0ba85e21bab
md"""
# Start setting things up
"""
# ╔═╡ 08ef7fbf-005b-40b5-acde-f42750c04cd3
begin
const tops = [
ConstellationOperator(payoff1,em2_a,value_function_generator())
,ConstellationOperator(payoff1,em2_b,value_function_generator())
,ConstellationOperator(payoff1,em2_c,value_function_generator())
,ConstellationOperator(payoff1,em2_d,value_function_generator())
]
#sanity Check time
@assert length(tops) == N_constellations "Mismatch in predetermined number of constellations and the number of operators initialized"
end
# ╔═╡ 43b99708-0052-4b78-886c-92ac2b532f29
begin #testing
Ξ(s1,d1,bm,tops[1],collected_policies)
end
# ╔═╡ 89258b2e-cee5-4cbd-a42e-21301b7a2549
begin
#=
This struct organizes information about a given constellation operator
Used to provide an interable loss function for training
=#
struct OperatorLoss
physical_model::PhysicalParameters
co::ConstellationOperator
collected_policies::Flux.Chain
policy_params::Flux.Params
struct ConstellationOperatorLoss
#econ model describing operator
econ_model::EconomicModel
#Operator's value and policy functions, as well as which parameters the operator can train.
operator_value_fn::Flux.Chain
collected_policies::Flux.Chain #this is held by all operators
operator_policy_params::Flux.Params
#Transition functions
debris_transition::BasicDebrisEvolution
stocks_transition::BasicStockEvolution
end
function (self::OperatorLoss)(
# overriding function to calculate operator loss
function (operator::ConstellationOperatorLoss)(
s::Vector{Float32}
,d::Vector{Float32}
; #set default policy to the one held by the ConstellationOperator
policy::Flux.Chain = operator.collected_policies
)
Ξ(s ,d ,self.physical_model ,self.co ,self.collected_policies )
#get actions
a = policy((s,d))
#get updated stocks and debris
s′ = stocks_transition(s ,d ,a)
d′ = debris_transition(s ,d ,a)
bellman_residuals = operator.operator_value_fn((s,d)) - operator.econ_model(s,d,a) - operator.econ_model.β * operator.operator_value_fn((s′,d′))
maximization_condition = - operator.econ_model(s,d,a,co.econ_params) - co.econ_params.β*co.value((s′,d′))
return sum(bellman_residuals.^2, maximization_condition)
end
#do the same thing with the planner's problem
struct PlannerLoss
#=
Ideally, with just a well formed PlannerLoss and the training functions below, we should be able to train the approximation.
There is an issue with appropriately training the value functions.
In this case, it is not happening...
=#
operators::Array{ConstellationOperatorLoss}
planner_policy::Flux.Chain
planner_params::Flux.Params
end
function planners_loss(
function (pl::PlannerLoss)(
s::Vector{Float32}
,d::Vector{Float32}
)
l = 0.0
for (i,co) in enumerate(tops)
l += Ξ(s,d,bm,tops,i)
for co in pl.operators
l += co(s ,d ,pl.planner_policy)
end
return l
end
#TODO: Training Functions as routines
end
# ╔═╡ cd55e232-493d-4849-8bd7-b0ba85e21bab
md"""
# Start setting things up
"""
# ╔═╡ 08ef7fbf-005b-40b5-acde-f42750c04cd3
begin
const tops = [
ConstellationOperator(payoff1,em2_a,value_function_generator())
,ConstellationOperator(payoff1,em2_b,value_function_generator())
,ConstellationOperator(payoff1,em2_c,value_function_generator())
,ConstellationOperator(payoff1,em2_d,value_function_generator())
]
#sanity Check time
@assert length(tops) == N_constellations "Mismatch in predetermined number of constellations and the number of operators initialized"
end
# ╔═╡ fb6aacff-c42d-4ec1-88cb-5ce1b2e8874f
policy = planner_policy_function_generator();
planner_policy = planner_policy_function_generator();
# ╔═╡ 5abebc1a-370c-4f5f-8826-dc0b143d5166
md"""
@ -1045,28 +1046,28 @@ uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"
# ╟─9fa41b7c-1923-4c1e-bfc6-20ce4a1a2ede
# ╟─0d209540-29ad-4b2f-9e91-fac2bbee47ff
# ╟─5b45b29e-f0f4-41e9-91e7-d444687feb4e
# ╟─152f3a3c-a565-41bb-8e59-6ab0d2315ffb
# ╟─25ac9438-2b1d-4f6b-9ff1-1695e1d52b51
# ╠═f8779824-9d59-4458-926f-10beb3cd3866
# ╠═152f3a3c-a565-41bb-8e59-6ab0d2315ffb
# ╠═25ac9438-2b1d-4f6b-9ff1-1695e1d52b51
# ╠═6bf01e30-d054-4a98-9e0d-58d7da4e5524
# ╠═9b1c2f62-ec19-4667-8f93-f8b52750e317
# ╟─90446134-4e45-471c-857d-4e165e51937a
# ╟─29ff1777-d276-4e8f-8582-4ca191f2e2ff
# ╠═f7aabe43-9a2c-4fe0-8099-c29cdf66566c
# ╠═d816b252-bdca-44ba-ac5c-cb21163a1e9a
# ╠═95bfc9d8-8427-41d6-9f0f-f155296eef91
# ╟─f7aabe43-9a2c-4fe0-8099-c29cdf66566c
# ╟─d816b252-bdca-44ba-ac5c-cb21163a1e9a
# ╠═ae6681e0-c796-4145-a313-75f74b4993ad
# ╠═bbca5143-f314-40ea-a20e-8a043272e362
# ╠═340da189-f443-4376-a82d-7699a21ab7a2
# ╠═206ac4cc-5102-4381-ad8a-777b02dc4d5a
# ╠═eebb8706-a431-4fd1-b7a5-40f07a63d5cb
# ╠═f8d582cb-10cf-4c72-8127-787f662e0567
# ╠═b433a7ec-8264-48d6-8b95-53d2ec4bad05
# ╠═65e0b1fa-d5e1-4ff6-8736-c9d6b5f40150
# ╠═19ccfc3a-6dbb-4c64-bf03-e2e219ef0efe
# ╠═dc614254-c211-4552-b985-03020bfc5ab3
# ╠═4452ab2c-813b-4b7b-8cb3-388ec507a24c
# ╠═5946daa3-4608-43f3-8933-dd3eb3f4541c
# ╠═41271ab4-1ec7-431f-9efb-0f7c3da2d8b4
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# ╠═43b99708-0052-4b78-886c-92ac2b532f29
# ╠═41271ab4-1ec7-431f-9efb-0f7c3da2d8b4
# ╠═89258b2e-cee5-4cbd-a42e-21301b7a2549
# ╠═cd55e232-493d-4849-8bd7-b0ba85e21bab
# ╠═08ef7fbf-005b-40b5-acde-f42750c04cd3

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