Rocco Ascone

dblp:353/2112 · DBLP profile ↗
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5ranked-venue papers
5as first author
5since 2021 · last 2025
0009-0006-1390-4967ORCID · corroborated

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Artificial intelligence and machine learning · 2 · 2 first-author · 2 since 2021Theory of computation · 2 · 2 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2025 Cycles and global attractors of reactantless and inhibitorless reaction systems
abstract
We explore the computational complexity of deciding the existence of fixed points and cycles that can be reached from any other states (called global attractors ) in the dynamics of inhibitorless and reactantless reaction systems. The problems we consider are all known to be PSPACE -complete in the case of unconstrained reaction systems; in this paper, we show that some of them become polynomially solvable when limited to inhibitorless and reactantless reaction systems, while others remain PSPACE -complete. Specifically, we prove that the problems of deciding (i) if a given state belongs to a cycle, (ii) whether two reaction systems have at least one cycle in common, and (iii) whether they have the same set of cycles, remain PSPACE -complete even in the inhibitorless and reactantless classes, as well as the problem of deciding if a global cycle attractor exists in a reactantless reaction system. Interestingly, however, we demonstrate that no global cycle attractor of length at least 2 can exist in inhibitorless reaction systems; and no global cycle attractor of length greater than 2 can exist in reactantless reaction systems. Furthermore, we show that the problems of deciding whether a given state is a global attractor and whether a global fixed point attractor exists become polynomially solvable when restricted to inhibitorless and reactantless reaction systems.
Rocco Ascone, Giulia Bernardini 0001, Luca Manzoni
Theor. Comput. Sci.1
2024 A Unifying Taxonomy of Pattern Matching in Degenerate Strings and Founder Graphs
abstract
Elastic Degenerate (ED) strings and Elastic Founder (EF) graphs are two versions of acyclic components of pangenomes. Both ED strings and EF graphs (which we collectively name variable strings) extend the well-known notion of indeterminate string. Recent work has extensively investigated algorithmic tasks over these structures, and over several other variable strings notions that they generalise. Among such tasks, the basic operation of matching a pattern into a text, which can serve as a toolkit for many pangenomic data analyses using these data structures, deserves special attention. In this paper we: (1) highlight a clear taxonomy within both ED strings and EF graphs ranging through variable strings of all types, from the linear string up to the most general one; (2) investigate the problem PvarT(X,Y) of matching a solid or variable pattern of type X into a variable text of type Y; (3) using as a reference the quadratic conditional lower bounds that are known for PvarT(solid,ED) and PvarT(solid,EF), for all possible types of variable strings X and Y we either prove the quadratic conditional lower bound for PvarT(X,Y), or provide non-trivial, often sub-quadratic, upper bounds, also exploiting the above-mentioned taxonomy.
Rocco Ascone, Giulia Bernardini 0001, Alessio Conte, Massimo Equi, Estéban Gabory, Roberto Grossi, Nadia Pisanti
WABI1
2024 Pure reaction automata
abstract
Abstract This work introduces the new class of pure reaction automata, as well as a new update manner, called maximal reactive manner, that can also be applied to standard reaction automata. Pure reaction automata differ from the standard model in that they don’t have permanence: the entities that are not consumed by the reactions happening at a certain state are not conserved in the result states. We prove that the set of languages accepted by the new class under the maximal reactive manner contains the set of languages accepted by standard reaction automata under the same manner or under the maximal parallel manner. We also prove that a strict subclass of pure reaction automata can compute any partial recursive function.
Rocco Ascone, Giulia Bernardini 0001, Enrico Formenti, Francesco Leiter, Luca Manzoni
Nat. Comput.1
2024 Fixed points and attractors of additive reaction systems
abstract
Abstract Reaction systems are discrete dynamical systems that simulate biological processes within living cells through finite sets of reactants, inhibitors, and products. In this paper, we study the computational complexity of deciding on the existence of fixed points and attractors in the restricted class of additive reaction systems, in which each reaction involves at most one reactant and no inhibitors. We prove that all the considered problems, that are known to be hard for other classes of reaction systems, are polynomially solvable in additive systems. To arrive at these results, we provide several non-trivial reductions to problems on a polynomially computable graph representation of reaction systems that might prove useful for addressing other related problems in the future.
Rocco Ascone, Giulia Bernardini 0001, Luca Manzoni
Nat. Comput.1
2024 Fixed points and attractors of reactantless and inhibitorless reaction systems
abstract
Reaction systems are discrete dynamical systems that model biochemical processes in living cells using finite sets of reactants, inhibitors, and products. We investigate the computational complexity of a comprehensive set of problems related to the existence of fixed points and attractors in two constrained classes of reaction systems, in which either reactants or inhibitors are disallowed. These problems have biological relevance and have been extensively studied in the unconstrained case; however, they remain unexplored in the context of reactantless or inhibitorless systems. Interestingly, we demonstrate that although the absence of reactants or inhibitors simplifies the system's dynamics, it does not always lead to a reduction in the complexity of the considered problems.
Rocco Ascone, Giulia Bernardini 0001, Luca Manzoni
Theor. Comput. Sci.1