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We consider the problem of learning a non-deterministic probabilistic system consistent with a given finite set of positive and negative tree samples. Consistency is defined with respect to strong simulation conformance. We propose learning…

Logic in Computer Science · Computer Science 2012-07-24 Anvesh Komuravelli , Corina S. Pasareanu , Edmund M. Clarke

Safe control of constrained linear systems under both epistemic and aleatory uncertainties is considered. The aleatory uncertainty characterizes random noises and is modeled by a probability distribution function (PDF) and the epistemic…

Systems and Control · Electrical Eng. & Systems 2022-10-28 Hamidreza Modares

Hyperproperties are a modern specification paradigm that extends trace properties to express properties of sets of traces. Temporal logics for hyperproperties studied in the literature, including HyperLTL, assume a synchronous semantics and…

Logic in Computer Science · Computer Science 2021-04-28 Laura Bozzelli , Adriano Peron , Cesar Sanchez

We consider systems whose lifetime is measured by the time of physical degradation of components, as well as the degree of power each component contributes to the system. The lifetimes of the components of the system are random variables.…

Probability · Mathematics 2025-01-27 Ismihan Bayramoglu

We present a graph theoretical approach to the configurational statistics of random tree-like objects, such as randomly branching polymers. In particular, for ideal trees we show that Pr\"ufer labelling provides: (i) direct access to the…

Statistical Mechanics · Physics 2025-12-02 Pieter H. W. van der Hoek , Angelo Rosa , Ralf Everaers

Signal Temporal Logic monitoring over numerical simulation traces has emerged as an effective approach to approximate verification of continuous and hybrid systems. In this report we explore an exact verification procedure for STL…

Logic in Computer Science · Computer Science 2020-08-18 Thomas Wright , Ian Stark

We introduce a 2-round stochastic constraint-satisfaction problem, and show that its approximation version is complete for (the promise version of) the complexity class AM. This gives a `PCP characterization' of AM analogous to the PCP…

Computational Complexity · Computer Science 2010-02-22 Andrew Drucker

We classify the complexity of the LTL satisfiability and model checking problems for several standard parameterisations. The investigated parameters are temporal depth, number of propositional variables and formula treewidth, resp.,…

Logic in Computer Science · Computer Science 2015-09-23 Martin Lück , Arne Meier

We show how program transformation techniques can be used for the verification of both safety and liveness properties of reactive systems. In particular, we show how the program transformation technique distillation can be used to transform…

Logic in Computer Science · Computer Science 2015-12-15 Geoff Hamilton

Probabilistic independence is a useful concept for describing the result of random sampling---a basic operation in all probabilistic languages---and for reasoning about groups of random variables. Nevertheless, existing verification methods…

Programming Languages · Computer Science 2020-07-21 Gilles Barthe , Justin Hsu , Kevin Liao

There seems to be a common prejudice that asymptotic safety is either incompatible with, or at best unrelated to, the other topics in the title. This is not the case. In fact, we show that 1) the existence of a fixed point with suitable…

High Energy Physics - Theory · Physics 2011-01-13 R. Percacci , G. P. Vacca

We show the existence of rigid combinatorial objects which previously were not known to exist. Specifically, for a wide range of the underlying parameters, we show the existence of non-trivial orthogonal arrays, $t$-designs, and $t$-wise…

Combinatorics · Mathematics 2017-03-14 Greg Kuperberg , Shachar Lovett , Ron Peled

One thing that discriminates living things from inanimate matter is their ability to generate similarly complex or non-random architectures in a large abundance. From DNA sequences to folded protein structures, living cells, microbial…

Other Quantitative Biology · Quantitative Biology 2018-02-07 Stuart M. Marshall , Alastair R. G. Murray , Leroy Cronin

When a property needs to be checked against an unknown or very complex system, classical exploration techniques like model-checking are not applicable anymore. Sometimes a~monitor can be used, that checks a given property on the underlying…

Formal Languages and Automata Theory · Computer Science 2015-07-07 Volker Diekert , Anca Muscholl , Igor Walukiewicz

In real-life scenarios, a Reinforcement Learning (RL) agent aiming to maximise their reward, must often also behave in a safe manner, including at training time. Thus, much attention in recent years has been given to Safe RL, where an agent…

Machine Learning · Statistics 2025-03-26 Edwin Hamel-De le Court , Francesco Belardinelli , Alexander W. Goodall

Application of discrete-time survival methods for continuous-time survival prediction is considered. For this purpose, a scheme for discretization of continuous-time data is proposed by considering the quantiles of the estimated event-time…

Machine Learning · Statistics 2019-10-16 Håvard Kvamme , Ørnulf Borgan

The region of attraction characterizes well-behaved and safe operation of a nonlinear system and is hence sought after for verification. In this paper, a framework for probabilistic region of attraction estimation is developed that combines…

Optimization and Control · Mathematics 2023-06-06 Torbjørn Cunis

We consider the problem of automatically inferring specifications in the branching-time logic, Computation Tree Logic (CTL), from a given system. Designing functional and usable specifications has always been one of the biggest challenges…

Logic in Computer Science · Computer Science 2023-10-24 Rajarshi Roy , Daniel Neider

Reliability (survival analysis, to biostatisticians) is a key ingredient for mak- ing decisions that mitigate the risk of failure. The other key ingredient is utility. A decision theoretic framework harnesses the two, but to invoke this…

Methodology · Statistics 2009-07-24 Nozer D. Singpurwalla

We present a formal proof in Lean of probably approximately correct (PAC) learnability of the concept class of decision stumps. This classic result in machine learning theory derives a bound on error probabilities for a simple type of…

Machine Learning · Computer Science 2021-01-11 Joseph Tassarotti , Koundinya Vajjha , Anindya Banerjee , Jean-Baptiste Tristan