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The wasteful consumption of freshwater in heavily populated coastal areas usually consist the basic reason for the intrusion of saltwater into the coastal aquifers. In order to avoid such catastrophic scenarios, their prediction is of utter significance. Underground water systems are highly complex and the water flow is extremely dynamic, thus making the prediction of this phenomenon a difficult task. For this reason, a two dimensional Cellular Automaton (CA) was designed enabling both the qualitative and quantitative simulation and illustration of the saltwater intrusion into an unconfined coastal aquifer. The presented results ensure the robustness of the proposed CA model taking full advantage of its inherent parallelism and local connectivity. [ABSTRACT FROM AUTHOR]

Man-made transport networks and their design are closely related to the shortest path problem and considered amongst the most debated problems of computational intelligence. Apart from using conventional or bio-inspired computer algorithms, many researchers tried to solve this kind of problem using biological computing substrates, gas-discharge solvers, prototypes of a mobile droplet, and hot ice computers. In this aspect, another example of biological computer is the plasmodium of acellular slime mould Physarum polycephalum (P. polycephalum), which is a large single cell visible by an unaided eye and has been proven as a reliable living substrate for implementing biological computing devices for computational geometry, graph-theoretical problems, and optimization and imitation of transport networks. Although P. polycephalum is easy to experiment with, computing devices built with the living slime mould are extremely slow; it takes slime mould days to execute a computation. Consequently, mapping key computing mechanisms of the slime mould onto silicon would allow us to produce efficient bio-inspired computing devices to tackle with hard to solve computational intelligence problems like the aforementioned. Toward this direction, a cellular automaton (CA)-based, Physarum-inspired, network designing model is proposed. This novel CA-based model is inspired by the propagating strategy, the formation of tubular networks, and the computing abilities of the plasmodium of P. polycephalum. The results delivered by the CA model demonstrate a good match with several previously published results of experimental laboratory studies on imitation of man-made transport networks with P. polycephalum. Consequently, the proposed CA model can be used as a virtual, easy-to-access, and biomimicking laboratory emulator that will economize large time periods needed for biological experiments while producing networks almost identical to the tubular networks of the real-slime mould. [ABSTRACT FROM PUBLISHER]

The recent discovery of the 'modern' memristor has drawn great attention of both academia and industry. Given their favorable performance merits, memristors are expected to play a fundamental role in electronic industry. Modeling of memristive devices is essential for circuit design, and a number of Simulation Program with Integrated Circuit Emphasis (SPICE) models have already been introduced. The common problem in most models is that there is no threshold consideration; hence, only a few address the nonlinear nature of the device. This paper aims to present a SPICE implementation of a threshold-type switching model of a voltage-controlled memristive device that attributes the switching effect to a tunneling distance modulation. Threshold-type switching is closer to the actual behavior of most experimentally realizable memristive systems, and our modeling approach addresses the issue of programming thresholds. Both the netlist and the simple schematic are provided, thus making it easy to comprehend and ready to be used. Compared with other modeling solutions, it involves significantly low-complexity operation under an unlimited set of frequencies, and its simulation results are in good qualitative and quantitative agreement with the theoretical formulation. The proposed model is used to simulate an antiserial memristive switch, proving that it can be efficiently introduced in complex memristive circuits. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In the last decade the amount of the stored data related to almost all areas of life has rapidly increased. However, the overall process of discovering knowledge from data demands more powerful clustering techniques to ensure that this knowledge is useful. In this paper, two nature inspired computation techniques, Cellular Automata (CA) and Ant Colonies are combined by taking advantage of their common prominent features, such as simplicity, locality and self organization. Inspired by the cellular ants algorithm of Vande Moere and Clayden which has designed for clustering purposes, a corresponding cellular ants model was developed in order to overcome some of the previous model limitations and to provide new insights in cellular ants based clustering. The presented simulation results prove the clustering efficiency of the proposed model in both qualitative and quantitative terms. [ABSTRACT FROM AUTHOR]

In this paper, an innovative bio-inspired unconventional approach to tackle with the Simultaneous Localization and Mapping (SLAM) task is presented. The proposed method draws inspiration from the slime mold Physarum polycephalum by utilizing the computational tool of Cellu-lar Automata (CA). In particular, a fully autonomous robot, equipped only with an omni-directional camera, explores and maps successfully an indoor unknown terrain by adopting the behaviour of the micro-organism Physarum polycephalum, namely its olfaction, its propaga-tion and foraging process. The Physarum's sense of olfaction corre-sponds to the robots unique sensor, namely an omni-directional camera and the foraging as well as the movement procedure of the organism in terms of robots SLAM is matched with the detection and mapping of an unknown space and the movement strategy, respectively. Moreover, the diffusion field of the Plasmodium corresponds to the robots field of view. In order to evaluate the proposed approach several experiments are drawn, that indicate the ability of the presented model to effectively and efficiently achieve its goals. The obtained results were compared to the corresponding ones produced by the random movement algorithm as well as by an exhaustive search algorithm. In all the examined cases, the presented simulation results reveal the strength and the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

This article presents a study regarding the increasing complexity of computer networks calls for developing new models for their simulation. It examines a system for modeling and simulation of computer networks based on cellular automata. It discusses that system reliability evaluation, algorithms for connectivity evaluation, and shortest path computation in a computer network have been implemented. The system was developed and designed as an interactive tool that offers automated modeling with the assistance of a dynamic and user-friendly graphical environment.

Computational functionality has been implemented successfully on chemical reactions in living systems. In the case of Belousov–Zhabotinsky (BZ) reaction, this was achieved by using collision-based techniques and by exploiting the light sensitivity of BZ. In order to unveil the computational capacity of the light sensitive BZ medium and the possibility to implement re-configurable logic, the design of multiple logic gates in a fixed BZ reservoir was investigated. The three basic logic gates (namely NOT, OR and AND) were studied to prove the Turing completeness of the architecture. Namely, all possible Boolean functions can be implemented as a combination of these logic gates. Nonetheless, a more complicated logic function was investigated, aiming to illustrate further capabilities of a fixed size BZ reservoir. The experiments executed within this study were implemented with a Cellular Automata (CA)-based model of the Oregonator equations that simulate excitation and wave propagation on a light sensitive BZ thin film. Given that conventional or von Neumann architecture computations is proved possible on the proposed configuration, the next step would be the realization of unconventional types of computation, such as neuromorphic and fuzzy computations, where the chemical substrate may prove more efficient than silicon. • Chemical reactions in living systems can implement computational functions. • Belousov–Zhabotinsky reaction is light sensitive and that can achieves its control. • The design of multiple logic gates in a fixed BZ reservoir was investigated. • Three basic logic gates NOT, OR and AND were implemented in the fixed reservoir. • The possibility to implement re-configurable logic is proven. [ABSTRACT FROM AUTHOR]