In trying to use planning for decision support systems, there have been an array of automated planning techniques and softwares that we have tried to use. Here is a list of things we believe others might find useful:
- Playground for classical planning -- http://planning.domains/ (try out the editor --> import)
- Planning resources -- https://planning.wiki/
- Check out the section on additional resources.
- Responsive Slack channel to ask for help.
- Efficient planners:
- Fast Forward (FF): https://fai.cs.uni-saarland.de/hoffmann/ff.html
- Fast Downward (FD): http://www.fast-downward.org/
- Easy to modify and understand
- MIP Basics by Gurobi
- Convex Optimization Course by R. Tibshirani
- Non-convex Optimization by P. Jain and P. Kar
A quick guide to setup pytest for your python code. Convert your code into a package by using the following directory structure.
setup.py
src
-- /a/1.py
tests
-- test_a_1.py
The setup.py
file is configured as follows:
Generates a bipartite graph with vertex sets V1 an V2 and edge list E
\begin{figure}[t]
\centering
\begin{tikzpicture}
% V1
\foreach \i in {-2, -1, ..., 2} {
\node at (\i, 0) (v\i) {$v_{\i}$};
\fill (\i, -0.25) circle (1.5pt);
}
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