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The use of Cellular Automata (CA) in combination with Learning Automata (LA) has demonstrated effectiveness in handling hard-to-be-solved problems. Due to their capacity to learn and adapt, as well as their inherent parallelism, they can expedite the problem-solving process for a range of problems, such as challenging logic puzzles. One such puzzle is Sudoku, which poses a combinatorial optimization challenge of great difficulty and complexity. In this study, a Sudoku puzzle was represented as an Irregular Learning Cellular Automaton (ILCA), using a reward and penalty algorithm to resolve it. Simulations for an amount of 400 puzzles were performed, while the results demonstrate that the proposed algorithm operates effectively, highlighting the concurrent and learning capabilities of the ILCA structure. Furthermore, two different performance enhancement methods are investigated, namely learning rates method and selective probability reset rule, which are able to increase the initial performance by 26.8 % and to achieve an overall 99.3 % resolution rate. [ABSTRACT FROM AUTHOR]

A kombucha is a tea and sugar fermented by over sixty kinds of yeasts and bacteria. This symbiotic community produces kombucha mats, which are cellulose-based hydrogels. The kombucha mats can be used as an alternative to animal leather in industry and fashion once they have been dried and cured. Prior to this study, we demonstrated that living kombucha mats display dynamic electrical activity and distinct stimulating responses. For use in organic textiles, cured mats of kombucha are inert. To make kombucha wearables functional, it is necessary to incorporate electrical circuits. We demonstrate that creating electrical conductors on kombucha mats is possible. After repeated bending and stretching, the circuits maintain their functionality. In addition, the abilities and electronic properties of the proposed kombucha, such as being lighter, less expensive, and more flexible than conventional electronic systems, pave the way for their use in a diverse range of applications. [ABSTRACT FROM AUTHOR]

In this study, we introduce an application of a Cellular Automata (CA)-based system for monitoring and estimating the spread of epidemics in real world, considering the example of a Greek city. The proposed system combines cellular structure and graph representation to approach the connections among the area's parts more realistically. The original design of the model is attributed to a classical SIR (Susceptible–Infected–Recovered) mathematical model. Aiming to upgrade the application's effectiveness, we have enriched the model with parameters that advances its functionality to become self-adjusting and more efficient of approaching real situations. Thus, disease-related parameters have been introduced, while human interventions such as vaccination have been represented in algorithmic manner. The model incorporates actual geographical data (GIS, geographic information system) to upgrade its response. A methodology that allows the representation of any area with given population distribution and geographical data in a graph associated with the corresponding CA model for epidemic simulation has been developed. To validate the efficient operation of the proposed model and methodology of data display, the city of Eleftheroupoli, in Eastern Macedonia—Thrace, Greece, was selected as a testing platform (Eleftheroupoli, Kavala). Tests have been performed at both macroscopic and microscopic levels, and the results confirmed the successful operation of the system and verified the correctness of the proposed methodology. [ABSTRACT FROM AUTHOR]

Cellular automata (CA) have been used to simulate a variety of different chemical, biological and physical phenomena. Their ability to emulate complex dynamics, emerging from simple local interactions of their elementary cells, made them a strong candidate for mimicking these phenomena, especially when accelerated computation through parallelization is required. Belousov–Zhabotinsky (BZ) is a class of chemical reactions that due to their potential as nonlinear chemical oscillators, have inspired scientists to use them as chemical computers. The Oregonator equations, which approximate the dynamics of BZ reactions, were implemented here using CA methods. This new modelling approach (CA-based Oregonator) was tested in terms of accuracy and efficiency against previous models and laboratory-based experimental results, while the benefits of this method were outlined. It was observed that the results from the CA-based Oregonator are in good agreement with both modelled and laboratory experiments. The main advantage of this method can be summarized as the acceleration achieved in current implementations (serial computers), but also towards potential future implementations in massively parallel computational systems (like field-programmable gate array hardware and nano-neuromorphic circuits) that have been proved to be good substrates for accelerating the implemented CA models. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1038/s41598-023-36244-8. Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-023-36244-8, published online 09 June 2023 The original version of this Article contained an error in the spelling of the author Pasquale D'Angelo which was incorrectly given as Passquale D'Angelo. [Extracted from the article]

Various synchronization algorithms have been introduced in literature during the last decades to deal with the firing squad synchronization problem on cellular automata (CA). Among others defective CA algorithms, where the CA cell is able to transmit information without previous processing, have been also presented. In our case, originating from the classical Mazoyer’s paper, where a minimum-time solution is presented with 6 states, a one-dimensional CA where one cell may permanently fail is presented. In the proposed algorithm, the defective cell can neither process nor transmit information any longer, while it is considered that such dynamic defects may become apparent in any time step of computation. A thorough analysis of the synchronization, in terms of location and time at which cell fails, for the cells found in both sides of defective cell is delivered to decipher the corresponding maximal possible number of synchronized cells in each part of the cut, due to defect, CA array. The proposed algorithm is properly extended to consider more than one defective cells that may occur in the under study one-dimensional CA. Based on the aforementioned analysis, we provide the generalization of synchronization with multiple totally defective cells, while application examples of the generalized CA algorithm in case of two defective cells are also presented. Finally, another intriguing aspect refers to handling of states that could be tentatively characterized as unknown, in a confrontation similar to the previous defective state but also different, since now this(these) cell(s) are not stated as faulty but unknown. As a result, a new one-dimensional CA with less states, compared to the previous CA defective algorithms, able to synchronize the maximal possible number of cells in each part occurs. [ABSTRACT FROM AUTHOR]

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach. [ABSTRACT FROM AUTHOR]