Imitative Attacker Deception in Stackelberg Security Games
Authors: Thanh Nguyen, Haifeng Xu
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experiments illustrate significant defender loss due to imitative attacker deception, suggesting the potential side effect of learning from the attacker. (Abstract) 5 Experiments We evaluate the solution quality of our proposed deceptive algorithm. |
| Researcher Affiliation | Academia | 1University of Oregon 2Harvard University |
| Pseudocode | No | The paper presents mathematical formulations (MINLP) but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions using 'GAMUT (http://gamut.stanford.edu/)' which is a third-party tool, but does not provide any links or statements for its own source code for the methodology described. |
| Open Datasets | No | The paper states that data is 'generated... using the covariance game generator, GAMUT (http://gamut.stanford.edu/)' but does not provide concrete access (link, DOI, citation) to a publicly available or open dataset that was used for training. |
| Dataset Splits | No | The paper states 'Each data point in our results is averaged over 250 different games' but does not provide specific details on training, validation, or test dataset splits or cross-validation setup. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., CPU/GPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper mentions the 'covariance game generator, GAMUT', but does not list any specific software or library names with version numbers that would be needed to replicate the experiment. |
| Experiment Setup | Yes | Each data point in our results is averaged over 250 different games (50 games per covariance value). Finally, we consider two scenarios: (i) small deceptive payoff space with an interval size of I = 1.0; and (ii) large space with I = 2.0. |