The complexity of software in embedded systems has increased significantly over the last years so that software verification now plays an important role in ensuring the overall pr...
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
Discrete event dynamic systems may have extremely large state spaces. For their analysis, it is usual to relax the description by removing the integrality constraints. Applying thi...
: In this paper, we present a sampling-based verification algorithm for continuous dynamic systems with uncertainty due to adversaries, unmodeled disturbance inputs, unknown parame...
We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamica...
Zhengzhu Feng, Richard Dearden, Nicolas Meuleau, R...