[HTML][HTML] Survey on mining signal temporal logic specifications
Formal specifications play an essential role in the life-cycle of modern systems, both at the
time of their design and during their operation. Despite their importance, formal …
time of their design and during their operation. Despite their importance, formal …
Scalable anytime algorithms for learning fragments of linear temporal logic
Linear temporal logic (LTL) is a specification language for finite sequences (called traces)
widely used in program verification, motion planning in robotics, process mining, and many …
widely used in program verification, motion planning in robotics, process mining, and many …
Active finite reward automaton inference and reinforcement learning using queries and counterexamples
Despite the fact that deep reinforcement learning (RL) has surpassed human-level
performances in various tasks, it still has several fundamental challenges. First, most RL …
performances in various tasks, it still has several fundamental challenges. First, most RL …
Synthesizing efficiently monitorable formulas in metric temporal logic
In runtime verification, manually formalizing a specification for monitoring system executions
is a tedious and error-prone process. To address this issue, we consider the problem of …
is a tedious and error-prone process. To address this issue, we consider the problem of …
Bridging ltlf inference to GNN inference for learning ltlf formulae
Learning linear temporal logic on finite traces (LTLf) formulae aims to learn a target formula
that characterizes the high-level behavior of a system from observation traces in planning …
that characterizes the high-level behavior of a system from observation traces in planning …
Maxsat-based temporal logic inference from noisy data
We address the problem of inferring descriptions of system behavior using temporal logic
from a finite set of positive and negative examples. In this paper, we consider two formalisms …
from a finite set of positive and negative examples. In this paper, we consider two formalisms …
Differentiable inference of temporal logic formulas
We demonstrate the first recurrent neural network architecture for learning signal temporal
logic (TL) formulas, and present the first systematic comparison of formula inference …
logic (TL) formulas, and present the first systematic comparison of formula inference …
PURLTL: Mining LTL Specification from Imperfect Traces in Testing
Formal specifications are widely used in software testing approaches, while writing such
specifications is a time-consuming job. Recently, a number of methods have been proposed …
specifications is a time-consuming job. Recently, a number of methods have been proposed …
Learning linear temporal properties for autonomous robotic systems
E Ghiorzi, M Colledanchise, G Piquet… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
The problem of passive learning of linear temporal logic formulae consists in finding the best
explanation for how two sets of execution traces differ, in the form of the shortest formula that …
explanation for how two sets of execution traces differ, in the form of the shortest formula that …
TempAMLSI: temporal action model learning based on STRIPS translation
Hand-encoding PDDL domains is generally considered difficult, tedious and error-prone.
The difficulty is even greater when temporal domains have to be encoded. Indeed, actions …
The difficulty is even greater when temporal domains have to be encoded. Indeed, actions …