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Planner failed to choose an action #20

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jkwwwwow opened this issue Jun 12, 2020 · 2 comments
Open

Planner failed to choose an action #20

jkwwwwow opened this issue Jun 12, 2020 · 2 comments

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@jkwwwwow
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When I try to run this program, I receive the following error message:

ERROR: LoadError: Planner failed to choose an action because the following exception was thrown:
The lower and upper bounds for the root belief were both 99.59999999999911, so no tree was created.

Use the default_action solver parameter to specify behavior for this case.


To specify an action for this case, use the default_action solver parameter.

Stacktrace:
 [1] action_info(::DESPOTPlanner{Speed_Planner_POMDP,IndependentBounds{DefaultPolicyLB{FunctionPolicy{var"#13#15"},Int64,ARDESPOT.var"#19#21"},typeof(golf_cart_upper_bound)},MemorizingSource{MersenneTwister},MersenneTwister}, ::SparseCat{Array{Any,1},Array{Float64,1}}) at /home/jkwwwwow/.julia/packages/ARDESPOT/thdGA/src/pomdps_glue.jl:17
 [2] action(::DESPOTPlanner{Speed_Planner_POMDP,IndependentBounds{DefaultPolicyLB{FunctionPolicy{var"#13#15"},Int64,ARDESPOT.var"#19#21"},typeof(golf_cart_upper_bound)},MemorizingSource{MersenneTwister},MersenneTwister}, ::SparseCat{Array{Any,1},Array{Float64,1}}) at /home/jkwwwwow/.julia/packages/ARDESPOT/thdGA/src/pomdps_glue.jl:38
 [3] get_best_possible_action(::Array{Int64,1}, ::Array{Int64,1}, ::Array{Int64,1}, ::Array{Int64,1}, ::Array{Float64,1}, ::Array{Int64,1}) at /home/jkwwwwow/autonomous_golf_cart/pomdp_python_integration/speed_planner_updated.jl:426
 [4] top-level scope at /home/jkwwwwow/autonomous_golf_cart/pomdp_python_integration/speed_planner_updated.jl:443
 [5] include(::Module, ::String) at ./Base.jl:377
 [6] exec_options(::Base.JLOptions) at ./client.jl:288
 [7] _start() at ./client.jl:484
in expression starting at /home/jkwwwwow/autonomous_golf_cart/pomdp_python_integration/speed_planner_updated.jl:443

I'm not sure whether there is a problem with ARDESPOT or a bug in the program.

@zsunberg
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The upper and lower bounds for the current belief were the same (I'm guessing it was really close to the goal). In this case, there is not really a clean way for the algorithm to determine the best action for an arbitrary pomdp. If you can think of a way to do that, please suggest it! You can specify a default action for this case with a function default_action(pomdp, b, ex) where ex is the exception.

@zsunberg
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zsunberg commented Jun 13, 2020

default_action is documented here: https://github.com/JuliaPOMDP/BasicPOMCP.jl/blob/master/src/BasicPOMCP.jl#L95 (sorry there's not a good way to find that doc, haha)

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