Equilibrium Computation and Robust Optimization in Zero Sum Games With Submodular Structure

Authors: Bryan Wilder

AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Experimental results for network security games and a robust budget allocation problem confirm that our algorithm delivers near-optimal solutions and scales to much larger instances than was previously possible.
Researcher Affiliation Academia Bryan Wilder Department of Computer Science and Center for Artificial Intelligence in Society University of Southern California bwilder@usc.edu
Pseudocode Yes Algorithm 1 EQUATOR(BRI, FO, LO, u, c, K, r)
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets Yes Yahoo. 2007. Yahoo! webscope dataset ydata-ysm-advertiser-bidsv1 0. http://research.yahoo.com/Academic Relations.
Dataset Splits No The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning.
Hardware Specification No The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments.
Software Dependencies No The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment.
Experiment Setup Yes EQUATOR was run with K = 100, c = 60, u = 0.1.