Counterfactual Regret Minimization in Sequential Security Games

Authors: Viliam Lisy, Trevor Davis, Michael Bowling

AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We validate our approach on two security-inspired domains.
Researcher Affiliation Academia Department of Computing Science University of Alberta, Edmonton, AB, Canada T6G 2E8 {lisy,trdavis1,bowling}@ualberta.ca
Pseudocode Yes The pseudocode is presented in Figure 2.
Open Source Code No No explicit statement about providing access to the paper's own open-source code was found.
Open Datasets Yes Transit game (TG) is the game used for evaluation in (Bosansky et al. 2015). Ticket inspection game (IG) is based on (Jiang et al. 2013).
Dataset Splits No No explicit mention of training/test/validation dataset splits or cross-validation was found for the game environments described.
Hardware Specification No The paper mentions using 'the computing resources of Compute Canada and Calcul Quebec,' but no specific hardware details like GPU/CPU models are provided.
Software Dependencies Yes For solving LPs, we used IBM CPLEX 12.51.
Experiment Setup Yes The precision of CPLEX is by default set to 10-6.