A fault injection platform for learning AIOps models
Frank Bagehorn, Jesus Rios, et al.
iWOAR 2022
In domains such as homeland security, cybersecurity, and competitive marketing, it is frequently the case that analysts need to forecast actions by other intelligent agents that impact the problem of interest. Standard structured expert judgment elicitation techniques may fall short in this type of problem as they do not explicitly take into account intentionality. We present a decomposition technique based on adversarial risk analysis followed by a behavioural recomposition using discrete choice models that facilitate such elicitation process and illustrate its reasonable performance through behavioural experiments.
Frank Bagehorn, Jesus Rios, et al.
iWOAR 2022
Dennis Wei, Haoze Wu, et al.
AISTATS 2023
Felipe Maia Polo, Subha Maity, et al.
NeurIPS 2024
Vidushi Sharma, Maxwell Giammona, et al.
J. Chem. Inf. Model.