67 citations · 121 across the 5 of their papers we have counts for
7 papers
Neural Simplex Architecture
Dung T. Phan, Radu Grosu, Nils Jansen +3
We present the Neural Simplex Architecture (NSA), a new approach to runtime assurance that provides safety guarantees for neural controllers (obtained e.g. using reinforcement lear…
Neural State Classification for Hybrid Systems
Dung Phan, Nicola Paoletti, Timothy Zhang +3
We introduce the State Classification Problem (SCP) for hybrid systems, and present Neural State Classification (NSC) as an efficient solution technique. SCP generalizes the model…
How to Learn a Model Checker
Dung Phan, Radu Grosu, Nicola Paoletti +2
We show how machine-learning techniques, particularly neural networks, offer a very effective and highly efficient solution to the approximate model-checking problem for continuous…
Declarative vs Rule-based Control for Flocking Dynamics
Usama Mehmood, Nicola Paoletti, Dung Phan +6
The popularity of rule-based flocking models, such as Reynolds' classic flocking model, raises the question of whether more declarative flocking models are possible. This question…
A Component-Based Simplex Architecture for High-Assurance Cyber-Physical Systems
Dung Phan, Junxing Yang, Matthew Clark +4
We present Component-Based Simplex Architecture (CBSA), a new framework for assuring the runtime safety of component-based cyber-physical systems (CPSs). CBSA integrates Assume-Gua…
Model Checking Cyber-Physical Systems using Particle Swarm Optimization
Dung Phan, Scott A. Smolka, Radu Grosu +3
We present a novel approach to the problem of model checking cyber-physical systems. We transform the model checking problem to an optimization one by designing an objective functi…
A survey on unmanned aerial vehicle collision avoidance systems
Hung Pham, Scott A. Smolka, Scott D. Stoller +2
Collision avoidance is a key factor in enabling the integration of unmanned aerial vehicle into real life use, whether it is in military or civil application. For a long time there…