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20112026
most citedSafety Analysis for Vehicle Guidance Systems with Dynamic Fault Trees

59 citations · 458 across the 94 of their papers we have counts for

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Showing 2018Show all

7 papers · 1 filter

cs.AI2018★ 9 cited

The Partially Observable Games We Play for Cyber Deception

Mohamadreza Ahmadi, Murat Cubuktepe, Nils Jansen +3

Progressively intricate cyber infiltration mechanisms have made conventional means of defense, such as firewalls and malware detectors, incompetent. These sophisticated infiltratio…

cs.LO2018

Parameter-Independent Strategies for pMDPs via POMDPs

Sebastian Arming, Ezio Bartocci, Krishnendu Chatterjee +2

Markov Decision Processes (MDPs) are a popular class of models suitable for solving control decision problems in probabilistic reactive systems. We consider parametric MDPs (pMDPs)…

cs.LO2018

Sound Value Iteration

Tim Quatmann, Joost-Pieter Katoen

Computing reachability probabilities is at the heart of probabilistic model checking. All model checkers compute these probabilities in an iterative fashion using value iteration.…

cs.SE2018★ 16 cited

One Net Fits All: A unifying semantics of Dynamic Fault Trees using GSPNs

Sebastian Junges, Joost-Pieter Katoen, Marielle Stoelinga +1

Dynamic Fault Trees (DFTs) are a prominent model in reliability engineering. They are strictly more expressive than static fault trees, but this comes at a price: their interpretat…

cs.AI2018

Synthesis in pMDPs: A Tale of 1001 Parameters

Murat Cubuktepe, Nils Jansen, Sebastian Junges +2

This paper considers parametric Markov decision processes (pMDPs) whose transitions are equipped with affine functions over a finite set of parameters. The synthesis problem is to…

cs.PL2018

How long, O Bayesian network, will I sample thee? A program analysis perspective on expected sampling times

Kevin Batz, Benjamin Lucien Kaminski, Joost-Pieter Katoen +1

Bayesian networks (BNs) are probabilistic graphical models for describing complex joint probability distributions. The main problem for BNs is inference: Determine the probability…

cs.LO2018★ 43 cited

Quantitative Separation Logic - A Logic for Reasoning about Probabilistic Programs

Kevin Batz, Benjamin Lucien Kaminski, Joost-Pieter Katoen +2

We present quantitative separation logic (). In contrast to classical separation logic, employs quantities which evaluate to real numbers instead of pr…