This package was first made in the winter of 2015 in the state of Tempe at Arizona State University when I was working on a paper for AAMAS, 2016.
run.sh in the
src/DOBSS folders to see how an example
input.txt can be run.
cd ./src/DOBSS python BSG_miqp.py mtd_webapps_input
cd ./src/switch_cost_DOBSS python cost_BSG_miqp.py cost_BSSG_input.txt
cd ./src/ResourcesHomogeneousScheduleSingleton python BSG_multi_lp.py BSSG_input.txt
The above code provides you with the marginal probabilities. Use the following code to get the mixed strategy distribution (Uses code by Aubrey Clark).
[paper], use the following command:Strategy generation code for deep neural networks
cd ./src/DOBSS python BSG_miqp.py mtd_neuralnets_input