Papers

The intruder deduction problem is central to symbolic security-protocol analysis: it asks whether an attacker can derive a target message from observed messages using (cryptographic) operators available to the attacker. Although convergent rewrite systems provide canonical normal forms, deduction modulo convergent theories remains undecidable in general, and existing decidable fragments are often shaped by practical cryptographic examples. In this paper, we study deduction from a minimal structural perspective. When all function symbols are unary, terms collapse to words and deduction becomes a right-divisibility problem for semi-Thue systems: given words $u$ and $v$ decide whether there exists $w$ such that $wu \equiv_S v$. We investigate this problem for several classes of semi-Thue systems and prove, to the best of our knowledge, new decidability results for convergent prefix-erasing and convergent suffix-erasing systems. We then extend this perspective to term rewriting systems whose rules erase contexts while lifting selected subterms or variables. Although these classes suggest possible decidable generalisations beyond the unary setting, we show that deduction is already undecidable for a convergent simultaneous variable-lifting system. This exposes both the potential and the limits of extending the right-divisibility results to richer equational theories.

Most of the conventional implementations of regular expressions are based on backtracking. Such implementations are slow in the worst case, and thus, we would like to develop a better matching algorithm. However, it is nontrivial to provide an efficient matching algorithm that can deal with practical extensions including submatch addressing. This paper studies regular expression with lookaheads and negative lookaheads, abbreviated to REwLA. First, we propose a transformation from a REwLA of size $m$ to a deterministic finite automaton of $\mr{O}(2^{2^m})$ states. Next, we consider weighted regular expressions, which enable us to calculate submatch addressing. We propose a transformation from a weighted REwLA of size $m$ to a weighted nondeterministic finite automaton of $\mr{O}(2^{2^m})$ states.

Linear Temporal Logic (LTL) is one of the most widely adopted languages for specifying temporal extended objectives in AI, with applications ranging from reactive synthesis to stochastic planning in Markov decision processes and reinforcement learning. Traditionally, solving any of these problems requires translating the LTL specification to a nondeterministic automata on infinite words and then determinizing it, a step that is notoriously difficult in theory and in practice. Recent work has introduced LTLf+, which lifts the finite-trace logic LTLf to infinite traces. LTLf+ has the same expressive power as LTL, yet it retains most of the crucial advantages of its base logic LTLf. Most reasoning in LTLf+ rests on finite automata on finite words, for which we have not only a canonical minimal representation but also an efficient determinization procedure. In this work we present the first translation from LTL to LTLf+. We first normalize an LTL formula into the syntactic reactivity fragment of the Manna-Pnueli hierarchy, to create the general fragment-based shape of LTLf+. We then present linear translations for each individual component of that fragment. As a consequence of this translation, the expanding body of techniques developed for LTLf+ now becomes available to many AI problems currently formulated in LTL. We further show that this comes at no asymptotic cost, as the pipeline from LTL to automaton via LTLf+ remains doubly exponential.

In this paper, we consider the parameter synthesis and optimization problem for parametric Markov decision processes (pMDPs), the extension of classical MDPs where exact probability values are replaced by parametric expressions. Computing the rational function $f_{\lsf}$ that maps parameter valuations to the satisfaction value of a PRCTL property $\lsf$ is a computationally expensive task, particularly for pMDPs where the optimal policy may vary across the parameter space. We adopt the scenario approach to efficiently synthesize a probably approximately correct (PAC) approximation $\ApproxFunOfProperty{f}$ of $f_{\lsf}$: by sampling parameter configurations and solving a linear program, we obtain a polynomial approximation whose error margin $\margin$ is guaranteed, with prescribed confidence, for all but an $\errorRate$-fraction of the parameter domain under the sampling distribution. We further show how this PAC framework can be combined with statistical model checking (SMC), enabling the analysis of black-box parametric models. Building on the PAC approximation, we integrate the DIRECT (DIviding RECTangles) algorithm for derivative-free global optimization over the parameter space. We establish conditional optimality-gap guarantees: under explicit Lipschitz and PAC-good-set assumptions, the difference between the true optimum $f_{\lsf}(\parameters^{*})$ and the value found by DIRECT is bounded by a partition-diameter term and, in the PAC case, an additional approximation-error term. An empirical evaluation on 2997 benchmarks focuses on the new DIRECT-based optimization component. The results show that DIRECT variants solve fewer instances than the scenario optimizer, but on their common successful instances they often return slightly better objective values and usually run faster, while remaining close to the scenario values within the PAC margin.

We prove a graph-theoretical characterisation of finitely generated subgroups of Thompson's group $V$: a finitely generated group embeds in $V$ if and only if it admits a faithful context-free action, or equivalently if it belongs to the class CF-TR of transition groups of context-free graphs recently introduced by Matucci and the three last authors. Using this characterisation, we prove results in different directions: - All known examples of groups with co-context-free Word Problem do embed in $V$, providing evidence towards Lehnert's conjecture. - Each finitely generated subgroup of $V$ is either virtually abelian, or contains a free non-abelian semigroup. It follows that groups of intermediate growth do not embed in Thompson's $V$. We further study the relation between transition groups defined by graphs that are limits or covers of each others, and prove properties of transition groups of context-free graphs of polynomial growth. Finally, we prove that the Basilica and Hanoï Towers groups do not embed in $V$. This uses the geometry of Schreier graphs of the natural actions of these groups and of Thompson's $V$.