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From the 1 of 10 linked papers with an AI index.

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20242026
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cs.FL2026

Resolving Nondeterminism by Chance

Soumyajit Paul, David Purser, Sven Schewe +3

History-deterministic automata are those in which nondeterministic choices can be correctly resolved stepwise: there is a strategy to select a continuation of a run given the next…

cs.FL2025

Good-for-MDP State Reduction for Stochastic LTL Planning

Christoph Weinhuber, Giuseppe De Giacomo, Yong Li +2

We study stochastic planning problems in Markov Decision Processes (MDPs) with goals specified in Linear Temporal Logic (LTL). The state-of-the-art approach transforms LTL formulas…

cs.FL2025

Efficient Learning of Weak Deterministic Büchi Automata

Mona Alluwayma, Yong Li, Sven Schewe +1

We present an efficient Angluin-style learning algorithm for weak deterministic Büchi automata (wDBAs). Different to ordinary deterministic Büchi and co-Büchi automata, wDBAs ha…

cs.FL2025

Saturation Problems for Families of Automata

León Bohn, Yong Li, Christof Löding +1

Families of deterministic finite automata (FDFA) represent regular -languages through their ultimately periodic words (UP-words). An FDFA accepts pairs of words, where the firs…

cs.FL2025

Solving MDPs with LTLf+ and PPLTL+ Temporal Objectives

Giuseppe De Giacomo, Yong Li, Sven Schewe +2

The temporal logics LTLf+ and PPLTL+ have recently been proposed to express objectives over infinite traces. These logics are appealing because they match the expressive power of L…

cs.FL2024

DFAMiner: Mining minimal separating DFAs from labelled samples

Daniele Dell'Erba, Yong Li, Sven Schewe

We propose DFAMiner, a passive learning tool for learning minimal separating deterministic finite automata (DFA) from a set of labelled samples. Separating automata are an interest…