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Problem models for testing POMDPs.jl

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Error Matching Method actions() despite definition

clburks9 opened this issue · comments

commented

Recreating the LightDark1D problem in a 2D toy problem called D2Diffs. When the simulate command is run with arguments for rollout_sim, pomdp, planner, filter, and belief, the following error is thrown with respect to the function actions(::D2Diffs):

ERROR: LoadError: MethodError: no method matching actions(::D2Diffs)
Closest candidates are:
  actions(::POMDP, !Matched::Any) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/space.jl:51
  actions(::Union{MDP, POMDP}, !Matched::Any) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/space.jl:43
  actions(!Matched::TigerPOMDP) at /home/cohrint/.julia/packages/POMDPModels/oR8C3/src/TigerPOMDPs.jl:76
  ...
Stacktrace:
 [1] BasicPOMCP.POMCPTree(::D2Diffs, ::Int64) at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/BasicPOMCP.jl:131
 [2] #action_info#4(::Bool, ::Function, ::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::ParticleCollection{Array{Float64,1}}) at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:5
 [3] action_info at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:2 [inlined]
 [4] action at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:19 [inlined]
 [5] simulate at /home/cohrint/.julia/packages/POMDPSimulators/xyfJM/src/rollout.jl:100 [inlined]
 [6] simulate(::RolloutSimulator{MersenneTwister}, ::D2Diffs, ::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::BasicParticleFilter{D2Diffs,D2Diffs,LowVarianceResampler,MersenneTwister,Array{Array,1}}, ::MvNormal{Float64,PDMats.PDiagMat{Float64,Array{Float64,1}},Distributions.ZeroVector{Float64}}) at /home/cohrint/.julia/packages/POMDPSimulators/xyfJM/src/rollout.jl:61
 [7] top-level scope at none:0
 [8] include at ./boot.jl:317 [inlined]
 [9] include_relative(::Module, ::String) at ./loading.jl:1044
 [10] include(::Module, ::String) at ./sysimg.jl:29
 [11] exec_options(::Base.JLOptions) at ./client.jl:231
 [12] _start() at ./client.jl:425
in expression starting at /home/cohrint/juliaPOMCP/D2DiffsTest.jl:170

This is despite the function being defined prior to the simulate call, show in the code posted below. Changes to the LightDark1D example which may affect something include the use of a 2D state and the lack of a defined struct for D2DiffsState and D2DiffsStateDist, passing a Multivariate normal to simulate instead.

import Base: ==, +, *, -

using POMDPs
using POMDPModels
using BasicPOMCP
using POMDPPolicies
using POMDPSimulators
using ParticleFilters
using Distributions
using Random



mutable struct D2Diffs <: POMDPs.POMDP{Array,Int,Int}
    discount_factor::Float64
    found_r::Float64
    lost_r::Float64
    step_size::Float64
    movement_cost::Float64
end




D2Diffs() = D2Diffs(0.9, 5.0, 0.0, 1.0, 0.0)

discount(p::D2Diffs) = p.discount_factor

initialstate_distribution(pomdp::D2Diffs) = MvNormal([10,10])


function observation(p::D2Diffs, sp::Array)
	if sqrt(s[1]*s[1] + s[2]*s[2]) < 1
		return 4
	elseif abs(s[1]) > abs(s[2])
		if s[1] < 0
			return 0
		else
			return 1
		end
	else
		if s[2] > 0
			return 2
		else
			return 3
		end
	end
end



function transition(p::D2Diffs, s::Array, a::Int)
	sig_0 = [1,1,0.00001,0.00001]
	#sig_stationary = [sqrt(0.00001),sqrt(0.00001),sqrt(0.00001),sqrt(0.00001)]
	d= MvNormal(sig_0)
    noise = rand(d::MvNormal) 


    if a == 0
        s= s + [-1,0,0,0] + noise
    elseif a == 1
        s= s + [1,0,0,0] + noise
    elseif a == 2
    	s= s + [0,1,0,0] + noise
    elseif a == 3
    	s= s + [0,-1,0,0] + noise
    else 
    	s= s + noise
    end

    s[1] = max(-10,s[1])
    s[1] = min(10,s[1]); 
    s[2] = max(-10,s[2])
    s[2] = min(10,s[2]);
    s[3] = max(0,s[3])
    s[3] = min(0,s[3]);
    s[4] = max(0,s[4])
    s[4] = min(0,s[4])

    return s   
    

end


function reward(p::D2Diffs, s::Array, a::Int)
   	if sqrt(s[1]*s[1] + s[2]*s[2]) < 1
		#return p.found_r
	else
		#return p.lost_r
	end
end;


convert_s(::Type{A}, s::Array, p::D2Diffs) where A<:AbstractArray = eltype(A)[s.status, s.y]
convert_s(::Type{Array}, s::A, p::D2Diffs) where A<:AbstractArray = Array(Int64(s[1]), s[2])



mutable struct DummyHeuristic1DPolicy <: POMDPs.Policy
    thres::Float64
end
DummyHeuristic1DPolicy() = DummyHeuristic1DPolicy(0.1)

mutable struct SmartHeuristic1DPolicy <: POMDPs.Policy
    thres::Float64
end
SmartHeuristic1DPolicy() = SmartHeuristic1DPolicy(0.1)



function action(p::SmartHeuristic1DPolicy, b::B) where {B}
	if sqrt(s[1]*s[1] + s[2]*s[2]) < 1
		return 4
	elseif abs(s[1]) > abs(s[2])
		if s[1] < 0
			return 0
		else
			return 1
		end
	else
		if s[2] > 0
			return 2
		else
			return 3
		end
	end
end


actions(::D2Diffs) = [0,1,2,3,4]
n_actions(p::D2Diffs) = length(actions(p))


println("Loaded Imports"); 

pomdp = D2Diffs()

println("Loaded Problem"); 

solver = POMCPSolver(); 

println("Loaded Solver"); 

planner = solve(solver, pomdp); 
rand_policy = RandomPolicy(pomdp);

println("Loaded Planner"); 

pf = SIRParticleFilter(pomdp,1000); 

println("Loaded Filter"); 

rollout_sim = RolloutSimulator(max_steps=10); 

println("Loaded Sim"); 

rollout_sim = RolloutSimulator(max_steps=10);
r_pomcp = simulate(rollout_sim, pomdp, planner, pf, MvNormal([10.,10.]));


@show r_pomcp;
commented

Hi @clburks9 ,

The error results because you have created a new function actions (or Main.actions) instead of creating a new method of POMDPs.actions.

Observe that the output of methods(actions) has only 1 method, while the output of methods(POMDPs.actions) has many methods, but none for D2Diffs

In order to create new methods of the interface functions in the POMDPs module, you need to import them with the import keyword instead of using, or qualify each new definition with POMDPs, e.g. POMDPs.actions(::D2Diffs) = [0,1,2,3,4].

More documentation can be found here: https://docs.julialang.org/en/v1/manual/modules/

You may also want to use this package: https://github.com/NTimmons/ImportAll.jl

Hope that all makes sense!

commented

@zsunberg , Thanks for the quick response!

Your suggestion fixed the error related to the actions function, but now I'm getting a similar, but slightly different error with the observation function. The methods(POMDPs.observation) returns a result with observation(::D2Diffs, s::Array). The error given below seems to be looking for a ::Float64 instead of an array.

ERROR: LoadError: MethodError: no method matching observation(::D2Diffs, ::Float64)
Closest candidates are:
  observation(::POMDP, ::Any, !Matched::Any) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/pomdp.jl:81
  observation(::POMDP, ::Any, !Matched::Any, !Matched::Any) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/pomdp.jl:90
  observation(!Matched::POMDPModelTools.FullyObservablePOMDP, ::Any, !Matched::Any) at /home/cohrint/.julia/packages/POMDPModelTools/eHEjm/src/fully_observable_pomdp.jl:23
  ...
Stacktrace:
 [1] observation(::D2Diffs, ::Int64, ::Float64) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/pomdp.jl:81
 [2] observation(::D2Diffs, ::Array{Float64,1}, ::Int64, ::Float64) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/pomdp.jl:90
 [3] macro expansion at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:92 [inlined]
 [4] generate_o(::D2Diffs, ::Array{Float64,1}, ::Int64, ::Float64, ::MersenneTwister) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:91
 [5] macro expansion at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:129 [inlined]
 [6] generate_so(::D2Diffs, ::Array{Float64,1}, ::Int64, ::MersenneTwister) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:127
 [7] macro expansion at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:168 [inlined]
 [8] generate_sor(::D2Diffs, ::Array{Float64,1}, ::Int64, ::MersenneTwister) at /home/cohrint/.julia/packages/POMDPs/JiYXY/src/generative_impl.jl:167
 [9] simulate(::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::Array{Float64,1}, ::BasicPOMCP.POMCPObsNode{Int64,Int64}, ::Int64) at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:90
 [10] search(::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::ParticleCollection{Array{Float64,1}}, ::BasicPOMCP.POMCPTree{Int64,Int64}, ::Dict{Symbol,Any}) at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:32
 [11] #action_info#4(::Bool, ::Function, ::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::ParticleCollection{Array{Float64,1}}) at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:6
 [12] action_info at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:2 [inlined]
 [13] action at /home/cohrint/.julia/packages/BasicPOMCP/01DOC/src/solver.jl:19 [inlined]
 [14] simulate at /home/cohrint/.julia/packages/POMDPSimulators/xyfJM/src/rollout.jl:100 [inlined]
 [15] simulate(::RolloutSimulator{MersenneTwister}, ::D2Diffs, ::POMCPPlanner{D2Diffs,BasicPOMCP.SolvedPORollout{RandomPolicy{MersenneTwister,D2Diffs,BeliefUpdaters.NothingUpdater},BeliefUpdaters.NothingUpdater,MersenneTwister},MersenneTwister}, ::BasicParticleFilter{D2Diffs,D2Diffs,LowVarianceResampler,MersenneTwister,Array{Array,1}}, ::MvNormal{Float64,PDMats.PDiagMat{Float64,Array{Float64,1}},Distributions.ZeroVector{Float64}}) at /home/cohrint/.julia/packages/POMDPSimulators/xyfJM/src/rollout.jl:61
 [16] top-level scope at none:0
 [17] include at ./boot.jl:317 [inlined]
 [18] include_relative(::Module, ::String) at ./loading.jl:1044
 [19] include(::Module, ::String) at ./sysimg.jl:29
 [20] exec_options(::Base.JLOptions) at ./client.jl:231
 [21] _start() at ./client.jl:425
in expression starting at /home/cohrint/juliaPOMCP/D2DiffsTest.jl:160
'''
commented
commented

Thank you! The error has been resolved

commented

Cool. Also, something to be aware of - having an abstract type or UnionAll like Arrayas your state type may result in very poor performance. Consider using a concrete type like Vector{Float64} or check out StaticArrays.jl for even better performance if the size is static.

I'm going to close this issue now since it appears to have been resolved.