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  • DNAQL: a query language for DNA sticker complexes
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-12
    Robert Brijder, Joris J. M. Gillis, Jan Van den Bussche

    DNA computing has a rich history of computing paradigms with great expressive power. However, far less expressive power is needed for data manipulation. Indeed, the relational algebra, the yardstick of database systems, is expressible in first-order logic, and thus less powerful than Turing-complete models. Turing-complete DNA computing models have to account for many and varied scenarios. A DNA implementation

  • The influence of fitness landscape characteristics on particle swarm optimisers
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-11
    A P Engelbrecht, P Bosman, K M Malan

    In the growing field of swarm-based metaheuristics, it is widely agreed that the behaviour of an algorithm, in terms of a good balance of exploration and exploitation, plays an important part in its success. Despite this, the influence that the characteristics of an optimisation problem may have on the behaviour of an algorithm is largely ignored. The characteristics of an optimisation problem can

  • A framework for designing of genetic operators automatically based on gene expression programming and differential evolution
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-09
    Dazhi Jiang, Zhihang Tian, Zhihui He, Geng Tu, Ruixiang Huang

    The design of genetic operators is absolutely one of the core work of evolutionary algorithms research. However, the essence of the evolutionary algorithms is that a lot of algorithm design is based on the manual result analysis, summarize, refine, feedback, and then, the algorithms are designed adaptively and correspondingly. This kind of design scheme needs artificial statistics and analysis of large

  • Improving convergence in swarm algorithms by controlling range of random movement
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-05
    Reshu Chaudhary, Hema Banati

    Swarm intelligence algorithms are stochastic algorithms, i.e. they perform some random movement. This random movement imparts the algorithms with exploration capabilities and allows them to escape local optima. Exploration at the start of execution helps with thorough inspection of the search/solution space. However, as the algorithm progresses, the focus should ideally shift from exploration to exploitation

  • DNA origami words, graphical structures and their rewriting systems
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-04
    James Garrett, Nataša Jonoska, Hwee Kim, Masahico Saito

    We classify rectangular DNA origami structures according to their scaffold and staples organization by associating a graphical representation to each scaffold folding. Inspired by well studied Temperley–Lieb algebra, we identify basic modules that form the structures. The graphical description is obtained by ‘gluing’ basic modules one on top of the other. To each module we associate a symbol such that

  • Stock market trend detection and automatic decision-making through a network-based classification model
    Nat. Comput. (IF 1.495) Pub Date : 2021-01-03
    Tiago Colliri, Liang Zhao

    Many complex systems observed in nature and society can be described in terms of network. A salient feature of networks is the presence of community patterns. Network-based models have already been applied in the analysis of data from very diverse areas, from epidemics modeling to periodicity detection in meteorological data. In this paper, inspired by the formation of community structures, such as

  • The fractal geometry of fitness landscapes at the local optima level
    Nat. Comput. (IF 1.495) Pub Date : 2020-12-19
    Sarah L. Thomson, Gabriela Ochoa, Sébastien Verel

    A local optima network (LON) encodes local optima connectivity in the fitness landscape of a combinatorial optimisation problem. Recently, LONs have been studied for their fractal dimension. Fractal dimension is a complexity index where a non-integer dimension can be assigned to a pattern. This paper investigates the fractal nature of LONs and how that nature relates to metaheuristic performance on

  • Reservoir computing quality: connectivity and topology
    Nat. Comput. (IF 1.495) Pub Date : 2020-12-15
    Matthew Dale, Simon O’Keefe, Angelika Sebald, Susan Stepney, Martin A. Trefzer

    We explore the effect of connectivity and topology on the dynamical behaviour of Reservoir Computers. At present, considerable effort is taken to design and hand-craft physical reservoir computers. Both structure and physical complexity are often pivotal to task performance, however, assessing their overall importance is challenging. Using a recently developed framework, we evaluate and compare the

  • Classifying Metaheuristics: Towards a unified multi-level classification system
    Nat. Comput. (IF 1.495) Pub Date : 2020-12-12
    Helena Stegherr, Michael Heider, Jörg Hähner

    Metaheuristics provide the means to approximately solve complex optimisation problems when exact optimisers cannot be utilised. This led to an explosion in the number of novel metaheuristics, most of them metaphor-based, using nature as a source of inspiration. Thus, keeping track of their capabilities and innovative components is an increasingly difficult task. This can be resolved by an exhaustive

  • A new taxonomy of global optimization algorithms
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-27
    Jörg Stork, A. E. Eiben, Thomas Bartz-Beielstein

    Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems. Still, it is difficult for practitioners to get an overview that explains their advantages in comparison to a large number of available methods in the scope of optimization. Available taxonomies lack the embedding of current

  • On computing the Lyapunov exponents of reversible cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-24
    Johan Kopra

    We consider the problem of computing the Lyapunov exponents of reversible cellular automata (CA). We show that the class of reversible CA with right Lyapunov exponent 2 cannot be separated algorithmically from the class of reversible CA whose right Lyapunov exponents are at most \(2-\delta\) for some absolute constant \(\delta >0\). Therefore there is no algorithm that, given as an input a description

  • On the use of $$(1,\lambda )$$ ( 1 , λ ) -evolution strategy as efficient local search mechanism for discrete optimization: a behavioral analysis
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-24
    Sara Tari, Matthieu Basseur, Adrien Goëffon

    A major issue while conceiving or parameterizing an optimization heuristic is to ensure an appropriate balance between exploitation and exploration of the search. Evolution strategies and neighborhood-based metaheuristics constitute relevant high-level frameworks, which ease the problem solving but are often complex to configure. Moreover, their effective behavior, according to the particularities

  • An Island Model based on Stigmergy to solve optimization problems
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-18
    Grasiele Regina Duarte, Afonso Celso de Castro Lemonge, Leonardo Goliatt da Fonseca, Beatriz Souza Leite Pires de Lima

    Island Model (IM) is an alternative often used to parallel Evolutionary Algorithms (EA). In IM, the population is distributed between islands that evolve their solutions in parallel, connected by a topology. Periodically, solutions migrate between islands according to a migration policy. The IM can be seen as an ideal structure to combine different algorithms to be used in an organized and cooperative

  • Complexity-theoretic aspects of expanding cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-10
    Augusto Modanese

    The expanding cellular automata (XCA) variant of cellular automata is investigated and characterized from a complexity-theoretical standpoint. An XCA is a one-dimensional cellular automaton which can dynamically create new cells between existing ones. The respective polynomial-time complexity class is shown to coincide with \({\le _{tt}^p}(\textsf {NP})\), that is, the class of decision problems polynomial-time

  • Improvement in learning enthusiasm-based TLBO algorithm with enhanced exploration and exploitation properties
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-10
    Nitin Mittal, Arpan Garg, Prabhjot Singh, Simrandeep Singh, Harbinder Singh

    Learning enthusiasm-based Teaching Learning Based Optimization (LebTLBO) is a metaheuristic inspired by the classroom teaching and learning method of TLBO. In recent years, it has been effectively used in several applications of science and engineering. In the conventional TLBO and most of its versions, all the learners have the same probability of getting knowledge from others. LebTLBO is motivated

  • Iterative arrays with self-verifying communication cell
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-05
    Martin Kutrib

    We study the computational capacity of self-verifying iterative arrays (\({\text {SVIA}}\)). A self-verifying device is a nondeterministic device whose nondeterminism is symmetric in the following sense. Each computation path can give one of the answers yes, no, or do not know. For every input word, at least one computation path must give either the answer yes or no, and the answers given must not

  • Absolute versus stochastic stability of the artificial bee colony in synchronous and sequential modes
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-04
    Sameh Kessentini, Ihcène Naâs

    The artificial bee colony (ABC) is a population-based optimization algorithm that mimics the foraging behavior of honeybees. Here, we focus on the parameter setting that ensures the ABC algorithm stability. Therefore, this paper introduces a matrix-iterative model, taking into account the coupling within bees. Moreover, the model considered the difference between update modes, i.e., synchronous or

  • Gamesourcing: an unconventional tool to assist the solution of the traveling salesman problem
    Nat. Comput. (IF 1.495) Pub Date : 2020-11-03
    Ivan Zelinka, Swagatam Das

    This paper presents an approach to solve the variant of the well-known Travelling Salesman Problem (TSP) by using a gamesourcing approach. In contemporary literature is TSP solved by wide spectra of modern as well as classical computational methods. We would like to point out the possibility to solve such problems by computer game plying that is called a gamesourcing. Gamesourcing can be understood

  • A study of model and hyper-parameter selection strategies for classifier ensembles: a robust analysis on different optimization algorithms and extended results
    Nat. Comput. (IF 1.495) Pub Date : 2020-10-30
    Antonino A. Feitosa-Neto, João C. Xavier-Júnior, Anne M. P. Canuto, Alexandre C. M. Oliveira

    It is well known that machine learning (ML) techniques have been playing an important role in several real world applications. However, one of the main challenges is the selection of the most accurate technique to be used in a specific application. In the classification context, for instance, two main approaches can be applied, model selection and hyper-parameter selection. In the first approach, the

  • Iterative arrays with finite inter-cell communication
    Nat. Comput. (IF 1.495) Pub Date : 2020-10-24
    Martin Kutrib, Andreas Malcher

    Iterative arrays whose internal inter-cell communication is quantitatively restricted are investigated. The quantity of communication is measured by counting the number of uses of the links between cells. In particular, iterative arrays are studied where the maximum number of communications per cell occurring in accepting computations is drastically bounded by a constant number. Additionally, the iterative

  • A comparison of multi-objective optimization algorithms for weight setting problems in traffic engineering
    Nat. Comput. (IF 1.495) Pub Date : 2020-10-23
    Vítor Pereira, Pedro Sousa, Miguel Rocha

    Traffic engineering approaches are increasingly important in network management to allow an optimized configuration and resource allocation. In link-state routing, setting appropriate weights to the links is an important and challenging optimization task. Different approaches have been put forward towards this aim, including evolutionary algorithms (EAs). This work addresses the evaluation of a single

  • A multi-level AI-based scheduler to increase adaptiveness in time-constrained mobile communication environments
    Nat. Comput. (IF 1.495) Pub Date : 2020-10-18
    Jesus Fernandez-Conde, Pedro Cuenca-Jimenez, Rafael Toledo-Moreo

    Scheduling is one of the classic problems in real-time adaptive systems. Due to the complex nature of these applications, the implementation of some sort of run-time intelligence is required, in order to build intelligent systems capable of operating adequately in dynamic environments. The incorporation of artificial intelligence planning techniques in a real-time scenario allows a timely reaction

  • An evaluation of k-means as a local search operator in hybrid memetic group search optimization for data clustering
    Nat. Comput. (IF 1.495) Pub Date : 2020-10-06
    Luciano D. S. Pacifico, Teresa B. Ludermir

    Cluster analysis is one important field in pattern recognition and machine learning, consisting in an attempt to distribute a set of data patterns into groups, considering only the inner properties of those data. One of the most popular techniques for data clustering is the K-Means algorithm, due to its simplicity and easy implementation. But K-Means is strongly dependent on the initial point of the

  • Correction to: A class of discrete dynamical systems with properties of both cellular automata and L-systems
    Nat. Comput. (IF 1.495) Pub Date : 2020-09-19
    Roderick Edwards, Aude Maignan

    In the pdf version of the original publication, in the proof of Theorem 8 (second column of p. 632), the T matrices appeared incorrectly. The correct values are given here.

  • The representational entity in physical computing
    Nat. Comput. (IF 1.495) Pub Date : 2020-09-18
    Susan Stepney, Viv Kendon

    We have developed abstraction/representation (AR) theory to answer the question “When does a physical system compute?” AR theory requires the existence of a representational entity (RE), but the vanilla theory does not explicitly include the RE in its definition of physical computing. Here we extend the theory by showing how the RE forms a linked complementary model to the physical computing model

  • Comparison of synchronous and asynchronous parallelization of extreme surrogate-assisted multi-objective evolutionary algorithm
    Nat. Comput. (IF 1.495) Pub Date : 2020-09-18
    Tomohiro Harada, Misaki Kaidan, Ruck Thawonmas

    This paper investigates the integration of a surrogate-assisted multi-objective evolutionary algorithm (MOEA) and a parallel computation scheme to reduce the computing time until obtaining the optimal solutions in evolutionary algorithms (EAs). A surrogate-assisted MOEA solves multi-objective optimization problems while estimating the evaluation of solutions with a surrogate function. A surrogate function

  • Protein structure prediction in an atomic model with differential evolution integrated with the crowding niching method
    Nat. Comput. (IF 1.495) Pub Date : 2020-09-10
    Daniel Varela, José Santos

    A hybrid version between differential evolution and the fragment replacement technique was defined for protein structure prediction. The coarse-grained atomic model of the Rosetta system was used for protein representation. The high-dimensional and multimodal nature of protein energy landscapes requires an efficient search for obtaining the native structures with minimum energy. However, the energy

  • Depicting probabilistic context awareness knowledge in deliberative architectures
    Nat. Comput. (IF 1.495) Pub Date : 2020-08-05
    Jonatan Ginés, Francisco J. Rodríguez-Lera, Francisco Martín, Ángel Manuel Guerrero, Vicente Matellán

    Facing long-term autonomy with a cognitive architecture raises several difficulties for processing symbolic and sub-symbolic information under different levels of uncertainty, and deals with complex decision-making scenarios. For reducing environment uncertainty and simplify the decision-making process, this paper establishes a method for translating robot knowledge to a conceptual graph to later extract

  • Benchmarking the performance of genetic algorithms on constrained dynamic problems
    Nat. Comput. (IF 1.495) Pub Date : 2020-07-22
    P. A. Grudniewski, A. J. Sobey

    The growing interest in dynamic optimisation has accelerated the development of genetic algorithms with specific mechanisms for these problems. To ensure that these developed mechanisms are capable of solving a wide range of practical problems it is important to have a diverse set of benchmarking functions to ensure the selection of the most appropriate Genetic Algorithm. However, the currently available

  • A memetic algorithm for restoring feasibility in scheduling with limited makespan
    Nat. Comput. (IF 1.495) Pub Date : 2020-07-06
    Raúl Mencía, Carlos Mencía, Ramiro Varela

    When solving a scheduling problem, users are often interested in finding a schedule optimizing a given objective function. However, in some settings there can be hard constraints that make the problem unfeasible. In this paper we focus on the task of repairing infeasibility in job shop scheduling problems with a hard constraint on the makespan. In this context, earlier work addressed the problem of

  • Hairpin completions and reductions: semilinearity properties
    Nat. Comput. (IF 1.495) Pub Date : 2020-06-27
    Henning Bordihn, Victor Mitrana, Andrei Păun, Mihaela Păun

    This paper is part of the investigation of some operations on words and languages with motivations coming from DNA biochemistry, namely three variants of hairpin completion and three variants of hairpin reduction. Since not all the hairpin completions or reductions of semilinear languages remain semilinear, we study sufficient conditions for semilinear languages to preserve their semilinearity property

  • Combining hyper-heuristics to evolve ensembles of priority rules for on-line scheduling
    Nat. Comput. (IF 1.495) Pub Date : 2020-06-08
    Francisco J. Gil-Gala, María R. Sierra, Carlos Mencía, Ramiro Varela

    Combining metaheuristics is a common technique that may produce high quality solutions to complex problems. In this paper, we propose a combination of Genetic Programming (GP) and Genetic Algorithm (GA) to obtain ensembles of priority rules to solve a scheduling problem, denoted \((1,Cap(t)||\sum T_i)\), on-line. In this problem, a set of jobs must be scheduled on a single machine whose capacity varies

  • Powering DNA strand-displacement reactions with a continuous flow reactor
    Nat. Comput. (IF 1.495) Pub Date : 2020-06-03
    Xinyu Cui, Dominic Scalise, Rebecca Schulman

    Living systems require a sustained supply of energy and nutrients to survive. These nutrients are ingested, transformed into low-energy waste products, and excreted. In contrast, synthetic DNA strand-displacement reactions typically run within closed systems provided with a finite initial supply of reactants. Once the reactants are consumed, all net reactions halt and the system ceases to function

  • Ensemble learning based on fitness Euclidean-distance ratio differential evolution for classification
    Nat. Comput. (IF 1.495) Pub Date : 2020-05-27
    Jing Liang, Yunpeng Wei, Boyang Qu, Caitong Yue, Hui Song

    Ensemble learning is a system that combines a set of base learners to improve the performance in machine learning, where accuracy and diversity of base learners are two important factors. However, these two factors are usually contradictory. To address this problem, in this paper, we propose a novel ensemble learning algorithm based on fitness Euclidean-distance ratio differential evolution, to train

  • An enhanced monarch butterfly optimization with self-adaptive crossover operator for unconstrained and constrained optimization problems
    Nat. Comput. (IF 1.495) Pub Date : 2020-05-21
    Mingyang Chen

    Inspired by the phenomenon of migration of monarch butterflies, Wang et al. developed a novel promising swarm intelligence algorithm, called monarch butterfly optimization (MBO), for addressing unconstrained low-dimensional optimization problems. In this paper, we firstly extend the application area of the basic MBO to solve the constrained optimization problems. At the same time, the crossover operator

  • Attractor landscapes in Boolean networks with firing memory: a theoretical study applied to genetic networks
    Nat. Comput. (IF 1.495) Pub Date : 2020-05-09
    Eric Goles; Fabiola Lobos; Gonzalo A. Ruz; Sylvain Sené

    In this paper we study the dynamical behavior of Boolean networks with firing memory, namely Boolean networks whose vertices are updated synchronously depending on their proper Boolean local transition functions so that each vertex remains at its firing state a finite number of steps. We prove in particular that these networks have the same computational power than the classical ones, i.e. any Boolean

  • Search space reduction of asynchrony immune cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2020-04-27
    Luca Mariot; Luca Manzoni; Alberto Dennunzio

    We continue the study of asynchrony immunity in cellular automata (CA), which can be considered as a generalization of correlation immunity in the case of vectorial Boolean functions. The property could have applications as a countermeasure for side-channel attacks in CA-based cryptographic primitives, such as S-boxes and pseudorandom number generators. We first give some theoretical results on the

  • Solving two-dimensional cutting stock problem via a DNA computing algorithm
    Nat. Comput. (IF 1.495) Pub Date : 2020-03-07
    M. Dodge, S. A. MirHassani, F. Hooshmand

    Two-dimensional cutting stock problem (TDCSP) is a well-known combinatorial optimization problem in which a given set of two-dimensional small pieces with different shapes should be cut from a given main board so that the demand of each small piece is satisfied and the total waste is minimized. Since TDCSP is an NP-complete problem, it is unsolvable in polynomial time on electronic computers. However

  • On the minimal number of generators of endomorphism monoids of full shifts
    Nat. Comput. (IF 1.495) Pub Date : 2020-02-14
    Alonso Castillo-Ramirez

    For a group G and a finite set A, denote by \(\mathrm{End}(A^G)\) the monoid of all continuous shift commuting self-maps of \(A^G\) and by \(\mathrm{Aut}(A^G)\) its group of units. We study the minimal cardinality of a generating set, known as the rank, of \(\mathrm{End}(A^G)\) and \(\mathrm{Aut}(A^G)\). In the first part, when G is a finite group, we give upper and lower bounds for the rank of \(\mathrm{Aut}(A^G)\)

  • The impact of alphabet size on pattern complexity of maxmin- $$\omega$$ω cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2020-04-14
    Ebrahim L. Patel

    We present an analysis of an additive cellular automaton (CA) under asynchronous dynamics. The asynchronous scheme is maxmin-\(\omega\), a deterministic system, introduced in our previous work with a binary alphabet. Extending this work, we study the impact of a larger alphabet, which also allows a meaningful inference of the behaviour of the resultant CA from the asymptotic behaviour of the maxmin-\(\omega\)

  • Perception of cloth in assistive robotic manipulation tasks
    Nat. Comput. (IF 1.495) Pub Date : 2020-02-12
    Pablo Jiménez; Carme Torras

    Assistive robots need to be able to perform a large number of tasks that imply some type of cloth manipulation. These tasks include domestic chores such as laundry handling or bed-making, among others, as well as dressing assistance to disabled users. Due to the deformable nature of fabrics, this manipulation requires a strong perceptual feedback. Common perceptual skills that enable robots to complete

  • Hybrid ant colony optimization algorithm applied to the multi-depot vehicle routing problem
    Nat. Comput. (IF 1.495) Pub Date : 2020-01-27
    Petr Stodola

    The article deals with the hybrid Ant Colony Optimization algorithm and its application to the Multi-Depot Vehicle Routing Problem (MDVRP). The algorithm combines both probabilistic and exact techniques. The former implements the bio-inspired approach based on the behaviour of ants in the nature when searching for food together with simulated annealing principles. The latter complements the former

  • A tutorial on elementary cellular automata with fully asynchronous updating
    Nat. Comput. (IF 1.495) Pub Date : 2020-01-23
    Nazim Fatès

    We present a panorama of the convergence properties of the 256 Elementary Cellular Automata under fully asynchronous updating, that is, when only one cell is updated at each time step. We regroup here various results which have been presented in different articles and expose a full analysis of the behaviour of finite systems with periodic boundary conditions. Our classification relies on the scaling

  • About block-parallel Boolean networks: a position paper
    Nat. Comput. (IF 1.495) Pub Date : 2020-01-03
    Jacques Demongeot; Sylvain Sené

    In automata networks, it is well known that the way entities update their states over time has a major impact on their dynamics. In particular, depending on the chosen update schedule, the underlying dynamical systems may exhibit more or less asymptotic dynamical behaviours such as fixed points or limit cycles. Since such mathematical models have been used in the framework of biological networks modelling

  • CRN ++: Molecular programming language
    Nat. Comput. (IF 1.495) Pub Date : 2020-01-03
    Marko Vasić; David Soloveichik; Sarfraz Khurshid

    Synthetic biology is a rapidly emerging research area, with expected wide-ranging impact in biology, nanofabrication, and medicine. A key technical challenge lies in embedding computation in molecular contexts where electronic micro-controllers cannot be inserted. This necessitates effective representation of computation using molecular components. While previous work established the Turing-completeness

  • Hierarchical growth is necessary and (sometimes) sufficient to self-assemble discrete self-similar fractals
    Nat. Comput. (IF 1.495) Pub Date : 2019-12-05
    Jacob Hendricks; Joseph Opseth; Matthew J. Patitz; Scott M. Summers

    In this paper, we prove that in the abstract Tile Assembly Model (aTAM), an accretion-based model which only allows for a single tile to attach to a growing assembly at each step, there are no tile assembly systems capable of self-assembling the discrete self-similar fractals known as the “H” and “U” fractals. We then show that in a related model which allows for hierarchical self-assembly, the 2-Handed

  • Forming tile shapes with simple robots
    Nat. Comput. (IF 1.495) Pub Date : 2019-12-03
    Robert Gmyr; Kristian Hinnenthal; Irina Kostitsyna; Fabian Kuhn; Dorian Rudolph; Christian Scheideler; Thim Strothmann

    Motivated by the problem of manipulating nanoscale materials, we investigate the problem of reconfiguring a set of tiles into certain shapes by robots with limited computational capabilities. As a first step towards developing a general framework for these problems, we consider the problem of rearranging a connected set of hexagonal tiles by a single deterministic finite automaton. After investigating

  • Transcript design problem of oritatami systems
    Nat. Comput. (IF 1.495) Pub Date : 2019-11-28
    Yo-Sub Han; Hwee Kim; Shinnosuke Seki

    RNA cotranscriptional folding refers to the phenomenon in which an RNA transcript folds upon itself while being synthesized out of a gene. Oritatami model is a computation model of this phenomenon, which lets its sequence (transcript) of beads (abstract molecules) fold cotranscriptionally by the interactions between beads according to its ruleset. We study the problem of designing a transcript that

  • Hierarchies and undecidability results for iterative arrays with sparse communication
    Nat. Comput. (IF 1.495) Pub Date : 2019-11-25
    Andreas Malcher

    Iterative arrays with restricted internal inter-cell communication are investigated. A quantitative measure for the communication is defined by counting the number of uses of the links between cells and it is differentiated between the sum of all communications of an accepting computation and the maximum number of communications per cell occurring in accepting computations. The computational complexity

  • Reversible causal graph dynamics: invertibility, block representation, vertex-preservation
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-24
    P. Arrighi; S. Martiel; S. Perdrix

    Causal Graph Dynamics extend Cellular Automata to arbitrary time-varying graphs of bounded degree. The whole graph evolves in discrete time steps, and this global evolution is required to have a number of symmetries: shift-invariance (it acts everywhere the same) and causality (information has a bounded speed of propagation). We add a further physics-like symmetry, namely reversibility. In particular

  • State-efficient realization of fault-tolerant FSSP algorithms
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-17
    Hiroshi Umeo; Naoki Kamikawa; Masashi Maeda; Gen Fujita

    The firing squad synchronization problem (FSSP, for short) on cellular automata has been studied extensively for more than fifty years, and a rich variety of FSSP algorithms has been proposed. Here we study the classical FSSP on a model of fault-tolerant cellular automata that might have possibly some defective cells and present the first state-efficient implementations of fault-tolerant FSSP algorithms

  • Turns of different angles and discrete-continuous pedestrian dynamics model
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-11
    Ekaterina Kirik; Tat’yana Vitova; Andrey Malyshev

    In the paper we discuss a problem of correct simulation of movement of the people on the pathes with angles. The shortest path strategy does not work in this cases and gives unrealistic trajectories and increased evacuation time. The discrete-continuous pedestrian dynamics model have been discussed. Angles from \(90^\circ\) to \(180^\circ\) were considered: “L”-, “Z”- and “U”-shaped geometries. A way

  • Optimal and suboptimal regional control of probabilistic cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-05
    Franco Bagnoli; Sara Dridi; Samira El Yacoubi; Raúl Rechtman

    Probabilistic cellular automata are extended stochastic systems, widely used for modelling phenomena in many disciplines. The possibility of controlling their behaviour is therefore an important topic. We shall present here an approach to the problem of controlling such systems by acting only on the boundary of a target region. In particular we are interested in optimal control, which is rather demanding

  • Lattice-based versus lattice-free individual-based models: impact on coexistence in competitive communities
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-04
    Aisling J. Daly; Ward Quaghebeur; Tim M. A. Depraetere; Jan M. Baetens; Bernard De Baets

    Individual-based modelling is an increasingly popular framework for modelling biological systems. Many of these models represent space as a lattice, thus imposing unrealistic limitations on the movement of the modelled individuals. We adapt an existing model of three competing species by using a lattice-free approach, thereby improving the realism of the spatial dynamics. We retrieve the same qualitative

  • A cellular automata based approach to track salient objects in videos
    Nat. Comput. (IF 1.495) Pub Date : 2019-10-04
    Luca Crociani; Giuseppe Vizzari; Antonio Carrieri; Stefania Bandini

    In this paper we present an algorithm to track the motion of a salient object using Cellular Automata (CA). The overall work, taking inspiration from recent research on insect sensory motor system, investigates the application of non conventional computer vision approaches to evaluate their effectiveness in fulfilling this task. The proposed system employs the Sobel operator to individual frames, performing

  • An overview of quantum cellular automata
    Nat. Comput. (IF 1.495) Pub Date : 2019-09-20
    P. Arrighi

    Quantum cellular automata are arrays of identical finite-dimensional quantum systems, evolving in discrete-time steps by iterating a unitary operator G. Moreover the global evolution G is required to be causal (it propagates information at a bounded speed) and translation-invariant (it acts everywhere the same). Quantum cellular automata provide a model/architecture for distributed quantum computation

  • From electric circuits to chemical networks
    Nat. Comput. (IF 1.495) Pub Date : 2019-09-16
    Luca Cardelli; Mirco Tribastone; Max Tschaikowski

    Electric circuits manipulate electric charge and magnetic flux via a small set of discrete components to implement useful functionality over continuous time-varying signals represented by currents and voltages. Much of the same functionality is useful to biological organisms, where it is implemented by a completely different set of discrete components (typically proteins) and signal representations

  • Glider automorphisms and a finitary Ryan’s theorem for transitive subshifts of finite type
    Nat. Comput. (IF 1.495) Pub Date : 2019-09-05
    Johan Kopra

    For any mixing SFT X we construct a reversible shift-commuting continuous map (automorphism) which breaks any given finite point of the subshift into a finite collection of gliders traveling into opposing directions. As an application we prove a finitary Ryan’s theorem: the automorphism group \({{\,\mathrm{Aut}\,}}(X)\) contains a two-element subset S whose centralizer consists only of shift maps.

  • Universal logic elements constructed on the Turing Tumble
    Nat. Comput. (IF 1.495) Pub Date : 2019-09-03
    Takahiro Tomita, Jia Lee, Teijiro Isokawa, Ferdinand Peper, Takayuki Yumoto, Naotake Kamiura

    This paper presents a mathematical model for a mechanical computer called the Turing Tumble. We show that our model called Turing Tumble Model (TTM) is computationally universal under the assumptions that a configuration of TTM is sufficiently large and that local interactions between elements can be transferred without limitations. The Turing Tumble has a strict constraint, based on gravity, since

  • The role of tessellation intersection in staggered quantum walks
    Nat. Comput. (IF 1.495) Pub Date : 2019-08-27
    Raqueline A. M. Santos

    The staggered quantum walk (SQW) model is defined by partitioning the graph into cliques, which are called polygons. We analyze the role that the size of the polygon intersection plays on the dynamics of SQWs on graphs. We introduce two processes (intersection reduction and intersection expansion), that change the number of vertices in some intersection of polygons, and we compare the behavior of the

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