arch2021_ainncs_re
Repeatability evaluation package for the ARCH2021 AI/NNCS competition
Science Score: 57.0%
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Low similarity (13.5%) to scientific vocabulary
Repository
Repeatability evaluation package for the ARCH2021 AI/NNCS competition
Basic Info
- Host: GitHub
- Owner: JuliaReach
- License: mit
- Language: Julia
- Default Branch: main
- Size: 298 KB
Statistics
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
ARCH2021 AINNCS
This is the JuliaReach repeatability evaluation (RE) package for the ARCH-COMP 2021 category report: Artificial Intelligence and Neural Network Control Systems (AINNCS) for Continuous and Hybrid Systems Plants of the 5th International Competition on Verifying Continuous and Hybrid Systems (ARCH-COMP '21).
To cite the work, you can use:
@inproceedings{JohnsonLBFGSICWL21,
author = {Taylor T. Johnson and
Diego Manzanas Lopez and
Luis Benet and
Marcelo Forets and
Sebasti{\'{a}}n Guadalupe and
Christian Schilling and
Radoslav Ivanov and
Taylor J. Carpenter and
James Weimer and
Insup Lee},
editor = {Goran Frehse and
Matthias Althoff},
title = {{ARCH-COMP21} Category Report: Artificial Intelligence and Neural
Network Control Systems {(AINNCS)} for Continuous and Hybrid Systems
Plants},
booktitle = {{ARCH}},
series = {EPiC Series in Computing},
volume = {80},
pages = {90--119},
publisher = {EasyChair},
year = {2021},
url = {https://doi.org/10.29007/kfk9},
doi = {10.29007/kfk9}
}
Installation
Note: Running the full benchmark suite should take no more than two hours with a reasonable internet connection.
There are two ways to install and run this RE: either using the Julia script or using the Docker script. In both cases, first clone this repository:
shell
$ git clone https://github.com/JuliaReach/ARCH2021_AINNCS.git
$ cd ARCH2021_AINNCS
Using the Julia script. First install the Julia language following the instructions here. Once you have installed Julia, execute
shell
$ julia startup.jl
to run all the benchmarks.
Using the Docker container.
To build the container, you need the program docker.
For installation instructions on different platforms, consult
the Docker documentation.
For general information about Docker, see
this guide.
Once you have installed Docker, start the measure_all script:
shell
$ ./measure_all
The Docker container can also be run interactively:
```shell $ docker run -it juliareach bash
$ julia
julia> include("startup.jl") ```
Outputs
After the benchmark runs have finished has finished, the results will be stored
in the folder result.
How the Julia environment was created
```julia julia> ]
(@v1.6) pkg> activate .
Activating new environment at .../ARCH2021_AINNCS/Project.toml
pkg> add https://github.com/sisl/NeuralVerification.jl#09b5c9f pkg> add https://github.com/JuliaReach/NeuralNetworkAnalysis.jl#b2f0255 pkg> add MAT pkg> add DifferentialEquations pkg> add Plots pkg> add Symbolics@0.1.32 ```
Owner
- Name: JuliaReach
- Login: JuliaReach
- Kind: organization
- Website: http://juliareach.com/
- Twitter: JuliaReach
- Repositories: 31
- Profile: https://github.com/JuliaReach
Reachability Computations for Dynamical Systems in Julia
Citation (CITATION.bib)
@inproceedings{JohnsonLBFGSICWL21,
author = {Taylor T. Johnson and
Diego Manzanas Lopez and
Luis Benet and
Marcelo Forets and
Sebasti{\'{a}}n Guadalupe and
Christian Schilling and
Radoslav Ivanov and
Taylor J. Carpenter and
James Weimer and
Insup Lee},
editor = {Goran Frehse and
Matthias Althoff},
title = {{ARCH-COMP21} Category Report: Artificial Intelligence and Neural
Network Control Systems {(AINNCS)} for Continuous and Hybrid Systems
Plants},
booktitle = {{ARCH}},
series = {EPiC Series in Computing},
volume = {80},
pages = {90--119},
publisher = {EasyChair},
year = {2021},
url = {https://doi.org/10.29007/kfk9},
doi = {10.29007/kfk9}
}
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| Name | Commits | |
|---|---|---|
| schillic | g****t@c****t | 2 |
| Christian Schilling | a****t@c****t | 1 |
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Dependencies
- julia 1.6.0 build