4 papers
DRMD: Deep Reinforcement Learning for Malware Detection under Concept Drift
Shae McFadden, Myles Foley, Mario D'Onghia +4
Malware detection in real-world settings must deal with evolving threats, limited labeling budgets, and uncertain predictions. Traditional classifiers, without additional mechanism…
Conformal Predictive Monitoring for Multi-Modal Scenarios
Francesca Cairoli, Luca Bortolussi, Jyotirmoy V. Deshmukh +2
We consider the problem of quantitative predictive monitoring (QPM) of stochastic systems, i.e., predicting at runtime the degree of satisfaction of a desired temporal logic proper…
LTL Verification of Memoryful Neural Agents
Mehran Hosseini, Alessio Lomuscio, Nicola Paoletti
We present a framework for verifying Memoryful Neural Multi-Agent Systems (MN-MAS) against full Linear Temporal Logic (LTL) specifications. In MN-MAS, agents interact with a non-de…
Certified Guidance for Planning with Deep Generative Models
Francesco Giacomarra, Mehran Hosseini, Nicola Paoletti +1
Deep generative models, such as generative adversarial networks and diffusion models, have recently emerged as powerful tools for planning tasks and behavior synthesis in autonomou…