/POMDPStressTesting.jl

Adaptive stress testing of black-box systems within POMDPs.jl

Primary LanguageJuliaOtherNOASSERTION

POMDPStressTesting.jl

Build Status Example Notebook codecov

Adaptive stress testing of black-box systems, implemented within the POMDPs.jl ecosystem.

Interface

To stress test a new system, the user has to define the GrayBox and BlackBox interface outlined in src/GrayBox.jl and src/BlackBox.jl.

GrayBox Interface

The GrayBox simulator and environment interface includes:

  • GrayBox.Simulation type to hold simulation variables
  • GrayBox.environment(sim::Simulation) to return the collection of environment distributions
  • GrayBox.transition!(sim::Simulation) to transition the simulator, returning the log-likelihood

BlackBox Interface

The BlackBox system interface includes:

  • BlackBox.initialize!(sim::Simulation) to initialize/reset the system under test
  • BlackBox.evaluate!(sim::Simulation) to evaluate/execute the system under test
  • BlackBox.distance(sim::Simulation) to return how close we are to an event
  • BlackBox.isevent(sim::Simulation) to indicate if a failure event occurred
  • BlackBox.isterminal(sim::Simulation) to indicate the simulation is in a terminal state

Functions ending with ! may modify the Simulation object in place.

Solvers

Several solvers are implemented.

Reinforcement learning solvers

Deep reinforcement learning solvers1

Stochastic optimization solvers

Baseline solvers

Example

An example implementation of the AST interface is provided for the Walk1D problem:

Installation

Install the required forked packages then the POMDPStressTesting.jl package:

using Pkg
pkg"registry add https://github.com/JuliaPOMDP/Registry"
pkg"add https://github.com/sisl/CrossEntropyMethod.jl"
pkg"add https://github.com/mossr/MCTS.jl"
pkg"add https://github.com/sisl/POMDPStressTesting.jl"

Contributing

We welcome contributions—please fork the repository and submit a new Pull Request with your changes.


Package maintained by Robert Moss: mossr@cs.stanford.edu

1 TRPO and PPO thanks to Shreyas Kowshik's initial implementation.