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pro vyhledávání: '"Mathiesen A"'
Autor:
Mathiesen, Frederik Baymler, Romao, Licio, Calvert, Simeon C., Laurenti, Luca, Abate, Alessandro
In this paper, we present a novel data-driven approach to quantify safety for non-linear, discrete-time stochastic systems with unknown noise distribution. We define safety as the probability that the system remains in a given region of the state spa
Externí odkaz:
http://arxiv.org/abs/2410.06662
Autor:
Espen Schaanning
Publikováno v:
Tidsskrift for Samfunnsforskning, Vol 61, Pp 410-413 (2020)
Externí odkaz:
https://doaj.org/article/6b7672f1200b489cb8da3f3cc7fb53b0
Autor:
Mjøset, Lars1
Publikováno v:
Acta Sociologica (Taylor & Francis Ltd). 1978, Vol. 21 Issue 3, p257-261. 5p.
Autor:
Mazouz, Rayan, Skovbekk, John, Mathiesen, Frederik Baymler, Frew, Eric, Laurenti, Luca, Lahijanian, Morteza
This paper introduces a method of identifying a maximal set of safe strategies from data for stochastic systems with unknown dynamics using barrier certificates. The first step is learning the dynamics of the system via Gaussian process (GP) regressi
Externí odkaz:
http://arxiv.org/abs/2405.00136
This paper presents a novel stochastic barrier function (SBF) framework for safety analysis of stochastic systems based on piecewise (PW) functions. We first outline a general formulation of PW-SBFs. Then, we focus on PW-Constant (PWC) SBFs and show
Externí odkaz:
http://arxiv.org/abs/2404.16986
Publikováno v:
Mitochondrial DNA. Part B. Resources, Vol 6, Iss 11, Pp 3261-3262 (2021)
Phlomoides rotata (Benth. ex Hook.f.) Mathiesen is a perennial herb endemic to Qinghai-Tibet Plateau with important medicinal properties. Here, we sequenced and analyzed the complete chloroplast (cp) genome of P. rotata and reconstructed the phylogen
Externí odkaz:
https://doaj.org/article/687e6e398209425b98308edafcd7197a
Akademický článek
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Autonomous vehicles rely on accurate trajectory prediction to inform decision-making processes related to navigation and collision avoidance. However, current trajectory prediction models show signs of overfitting, which may lead to unsafe or subopti
Externí odkaz:
http://arxiv.org/abs/2402.01397
In this paper, we present IntervalMDP.jl, a Julia package for probabilistic analysis of interval Markov Decision Processes (IMDPs). IntervalMDP.jl facilitates the synthesis of optimal strategies and verification of IMDPs against reachability specific
Externí odkaz:
http://arxiv.org/abs/2401.04068
Control Barrier Functions (CBFs) that provide formal safety guarantees have been widely used for safety-critical systems. However, it is non-trivial to design a CBF. Utilizing neural networks as CBFs has shown great success, but it necessitates their
Externí odkaz:
http://arxiv.org/abs/2311.10438