activity
20122026
most citedDamage detection using in-domain and cross-domain transfer learning

59 citations · 291 across the 45 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.LO2020

Adaptive Shielding under Uncertainty

Stefan Pranger, Bettina Könighofer, Martin Tappler +3

This paper targets control problems that exhibit specific safety and performance requirements. In particular, the aim is to ensure that an agent, operating under uncertainty, will…

cs.AI2020

Robust Finite-State Controllers for Uncertain POMDPs

Murat Cubuktepe, Nils Jansen, Sebastian Junges +3

Uncertain partially observable Markov decision processes (uPOMDPs) allow the probabilistic transition and observation functions of standard POMDPs to belong to a so-called uncertai…

cs.CV2020★ 7 cited

Adversarial Patch Camouflage against Aerial Detection

Ajaya Adhikari, Richard den Hollander, Ioannis Tolios +9

Detection of military assets on the ground can be performed by applying deep learning-based object detectors on drone surveillance footage. The traditional way of hiding military a…

cs.AI2020

Strengthening Deterministic Policies for POMDPs

Leonore Winterer, Ralf Wimmer, Nils Jansen +1

The synthesis problem for partially observable Markov decision processes (POMDPs) is to compute a policy that satisfies a given specification. Such policies have to take the full e…

cs.AI2020

Enforcing Almost-Sure Reachability in POMDPs

Sebastian Junges, Nils Jansen, Sanjit A. Seshia

Partially-Observable Markov Decision Processes (POMDPs) are a well-known stochastic model for sequential decision making under limited information. We consider the EXPTIME-hard pro…

cs.RO2020★ 45 cited

Formalizing and Guaranteeing* Human-Robot Interaction

Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman +12

Robot capabilities are maturing across domains, from self-driving cars, to bipeds and drones. As a result, robots will soon no longer be confined to safety-controlled industrial se…