51 citations · 366 across the 55 of their papers we have counts for
66 papers
Logic of Fuzzy Paths
Kush Grover, Pratham Gupta, Jan Křetínský
We introduce a new family of temporal logics intended for specifications in motion planning (MP). It builds upon the signal temporal logic (STL), which is a linear-time logic over…
SemML 2.0: Synthesizing Controllers for LTL
Jan Křetínský, Tobias Meggendorfer, Maximilian Prokop
Synthesizing a reactive system from specifications given in linear temporal logic (LTL) is a classical problem, finding its applications in safety-critical systems design. These sy…
Provably Explaining Neural Additive Models
Shahaf Bassan, Yizhak Yisrael Elboher, Tobias Ladner +4
Despite significant progress in post-hoc explanation methods for neural networks, many remain heuristic and lack provable guarantees. A key approach for obtaining explanations with…
Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions
Alessandro Abate, Giuseppe De Giacomo, Mathias Jackermeier +3
We study multi-task reinforcement learning (RL), a setting in which an agent learns a single, universal policy capable of generalising to arbitrary, possibly unseen tasks. We consi…
Sound Value Iteration for Simple Stochastic Games
Muqsit Azeem, Jan Kretinsky, Maximilian Weininger
Algorithmic analysis of Markov decision processes (MDP) and stochastic games (SG) in practice relies on value-iteration (VI) algorithms. Since basic VI does not provide guarantees…
SemML: Enhancing Automata-Theoretic LTL Synthesis with Machine Learning
Jan Kretinsky, Tobias Meggendorfer, Maximilian Prokop +1
Synthesizing a reactive system from specifications given in linear temporal logic (LTL) is a classical problem, finding its applications in safety-critical systems design. We prese…