Concept Of Automata Research Articles

Design of Web-Based Mathematical Knowledge Repository with LaTeX-like Format OFM

A repository of Mathematical Knowledge (MaKR) is designed as an individual tool, which also works as an assistant that helps thinking about the mathematical subjects. MaKR is a mathematical Web-based system whose contents are glued by an original LaTeX-like formatting language (low-)OFM that are designed under the concept of pushdown automaton, whose translator form OFM to HTML is written in Perl and named ofm2html. For the management of resources, a special-purpose Web browser called MaKRV is designed. Main topic in this paper is formatting language (low-)OFM.

Experimental analysis of the basic idea on the transcription-based diagnostic automata controlled by programmed molecules

Biomolecular computing using the artificial nucleic acid technology is expected to bring new solutions to various health problems. We focus on the noninvasive transcriptome diagnosis by salivary mRNAs and present the novel concept of transcription-based diagnostic automata that are constructed by programmed DNA modules. The main computational element has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by targets. Our system quantifies targets by transcription of malachite green aptamer sequence triggered by the target recognition. This algorithm makes it possible to realize the cost-effective and sequence-specific real-time target detection. Moreover, in the in-vivo therapeutic use, this transcription-based system can release RNA-aptamer drugs multiply at the transcription stage, different from the digestion-based systems by the restriction enzyme which was proposed previously. We verified the sensitivity, the selectivity and the quantitative stability of the diagnostic automata in basic conditions. Our approach will provide promising applications of autonomous intelligent systems using programmed molecules.

Encryption based on inverse iterating composition cellular automata system

The concepts of cross composition cellular automata and random composition cellular automata are introduced, and their feasibility in application to cryptosystem is analyzed. We use the inverse iteration of cellular automata to encrypt, and construct two encryption systems based on composition cellular automata. The new encryption systems effectively solve the problem of one way error diffusion in a single cellular automata system and acquire large key space with small rule radius. Simulation experiment shows that the diffusion and confusion properties of the new composition system are ideal, it resists brute attack and differential cryptanalysis.

Application service placement in stochastic grid environments using learning and ant-based methods

Achieving acceptable application performance in a grid environment remains a difficult challenge. In particular, this is true for applications composed of services that require certain criteria regarding quality to be fulfilled in order to satisfy users' needs. The problem considered here is the partitioning of application services onto the available execution nodes of a grid environment in such a way that they satisfy certain minimum criteria regarding quality. Fundamentally, this is an NP-hard problem. We propose three algorithms based on the concepts of learning automata and the metaphor of foraging ants. The algorithms naturally follow a decentralised multi-agent method for solving the service partitioning problem. Moreover, they establish a distributed problem-solving mechanism that does not require the use of a central controller. The proposed algorithms have been rigorously tested and evaluated through extensive simulations on randomly generated application services and grid environments. The results indicate that learning is an essential component for achieving scalability and efficiency in nature-inspired systems.

Embedding reach-scale fluvial dynamics within the CAESAR cellular automaton landscape evolution model

We introduce a new computational model designed to simulate and investigate reach-scale alluvial dynamics within a landscape evolution model. The model is based on the cellular automaton concept, whereby the continued iteration of a series of local process ‘rules’ governs the behaviour of the entire system. The model is a modified version of the CAESAR landscape evolution model, which applies a suite of physically based rules to simulate the entrainment, transport and deposition of sediments. The CAESAR model has been altered to improve the representation of hydraulic and geomorphic processes in an alluvial environment. In-channel and overbank flow, sediment entrainment and deposition, suspended load and bed load transport, lateral erosion and bank failure have all been represented as local cellular automaton rules. Although these rules are relatively simple and straightforward, their combined and repeatedly iterated effect is such that complex, non-linear geomorphological response can be simulated within the model. Examples of such larger-scale, emergent responses include channel incision and aggradation, terrace formation, channel migration and river meandering, formation of meander cutoffs, and transitions between braided and single-thread channel patterns. In the current study, the model is illustrated on a reach of the River Teifi, near Lampeter, Wales, UK.

Genetic algorithms and cellular automata in aquifer management

A groundwater management problem is presented involving pumping cost minimization with both well discharges and well locations as decision variables. A grid of candidate well locations is set up and optimal arrangements of wells are sought within this discrete space. A genetic algorithm approach is presented with the following particular features: (a) A suitable scaling is applied to the objective function in order to alleviate its regionally flat behavior. (b) No penalty functions are involved in constraint handling. Instead, the feasible region is transformed into a rectangular domain. The transformation introduced is proved to be bijective. (c) A binary representation of well configurations is presented and compared to a combinatorial one. The binary representation necessitates the introduction of specially designed genetic operators. Besides purely genetic algorithms, the concept of cellular automaton is introduced as the basis of an alternative formulation of the optimization problem. The lattice of the cellular automaton provides the discrete set of candidate well positions. The well configuration is represented by a group of agents occupying an equal number of lattice sites. The agents change positions as dictated by the structure of the automaton and, also, by an associated genetic algorithm, which directs the evolution of the whole scheme toward an optimal configuration. An improved performance of this approach is noted and discussed in comparison to the purely genetic algorithm schemes of the present work. A simulated annealing approach is also applied to the same problem for comparison purposes. Finally, a new and more efficient hybrid annealing–genetic approach is introduced and discussed.

Network-based train-following model and study of train’s delay propagation

Based on the cellular automaton concept, this paper presents a train-following model for the moving block system with different types of trains running. We apply the model to the rail network and simulate the running of trains. We also simulate the traffic phenomenon of delay propagation in moving block system. We investigate how the main factors including train deliver time interval and initial delay affect the delay propagation of trains. The simulation results are compared with the theoretical results to verity the reliabity and feasibility of the model.

General solutions to switching problems

The concept of switching automaton is introduced as a mathematical model for switching control in electric networks. The concepts of a system of switching rules and a switching problem are formalized. The general solutions to switching problems are investigated with the help of switching diagrams. The relation of switching diagrams and distributive lattices is established. A system of algebraic operations over switchings is defined. A general method of hierarchical decomposition of switching diagrams is presented.

Learning Design Engines as Remote Control to Learning Support Environments

Commentary on: Chapter5: An Architecture for Learning Design Engines. (Vogten, Koper, Martens and Tattersall, 2005) Abstract: Chapter 5 of the Learning Design book describes the operational model of a learning design engine based on the concept of finite automata with output alphabet. We rely on this event concept to include pre-existing learning tools in flexibe and rich learning designs. We sketch an approach for the integration of complex learning environments in learning designs. Interactive learning support environments, such as argumentation or modelling tools are pre-existent and have a high potential when integrated in learning designs. We propose an approach that aims at a clear separation of the learning design engine, the specification of the learning flow (as LD documents) and learning environments. According to its current state, the engine controls the learning environment with events (such as start a new phase), defined as a vocabulary for a set of environments, that are mapped to the environments' existing functionality (such as create new workspace). Thus the engine remotely controls the learning tools while the tools can initiate state transitions in the engine on specific events in the tool. Editors: Colin Tattersall and Rob Koper.

On the Minimality of Finite Automata and Stream X-machines for Finite Languages

A cover automaton of a finite language L is a finite automaton that accepts all words in L and possibly other words that are longer than any word in L. An algorithm for constructing a minimal cover automaton of a finite language L is given in a recent paper. This paper goes a step further by proposing a procedure for constructing all minimal cover automata of a given finite language L. The concept of cover automaton is then generalized to a form of extended finite automaton, the stream X-machine, and the procedure is extended to this more general model.

The accounting system as an algebraic automaton

This article aims to present a mathematical model to describe the accounting system. In effect, in the literature on accounting we can find several mathematical models trying to introduce the accounting mechanics but in this article we use the concept of algebraic automaton, which has been successfully used in other economic fields, like finance. Thus, from this new point of view we can construct all definitions and accounting techniques as a particular case of the concept of automaton. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 827–842, 2005.

On Modal μ-Calculus and Non-Well-Founded Set Theory

A finitary characterization for non-well-founded sets with finite transitive closure is established in terms of a greatest fixpoint formula of the modal μ-calculus. This generalizes the standard result in the literature where a finitary modal characterization is provided only for wellfounded sets with finite transitive closure. The proof relies on the concept of automaton, leading then to new interlinks between automata theory and non-well-founded sets.

Determinism and fuzzy automata

The concept of a fuzzy automaton, as studied in the literature, is a direct generalization of the classical concept of a non-deterministic automaton. In this paper, we consider the question of whether there is a deterministic counterpart to the notion of a fuzzy automaton. We propose a definition of deterministic fuzzy automata and show that they are equally powerful as fuzzy automata. Compared to the classical notion of a deterministic automaton, the deterministic fuzzy automaton defined in our paper differs essentially only in that the final states form a fuzzy set. Moreover, we show that deterministic fuzzy automata are equally powerful as nested systems of deterministic automata.

Performance assessment of adiabatic quantum cellular automata

We investigate the feasibility of an adiabatic logic scheme for cellular automaton systems recently proposed by Tóth and Lent [J. Appl. Phys. 85, 2977 (1999)], based on structured arrays of six-dot cells and on the use of a four-phase trapezoidal clock. With respect to the original quantum cellular automaton (QCA) concept, focused on ground state computation, a clocked scheme would have the advantage of being immune to the presence of metastable states and would allow pipelined operation, at the expense of additional complexity, due to the clock distribution circuitry. Based on realistic cell geometries and material systems, we have evaluated the obtainable switching times of QCA cells, and have determined the region in the parameter space that allows operation at a reasonable clock speed.

Structural design using cellular automata

This paper presents a shape and topology optimization scheme for structures by using the concept of a cellular automaton (CA). A design domain domain is divided into small square cells and then the thicknesses of the individual cells are taken as the design variables. Considering the cells as the finite elements, the stress analysis is performed by the finite element method. The design variables are modified by applying a local rule to the stress states of the cell and its neighbouring cells. The present scheme is applied to a two-dimensional elastic problem in order to confirm its validity.

Parallel dynamic programming and automata theory

Following Karp's discrete Dynamic Programming (DP) approach, this work extends the sequential model for monadic DP to the parallel case. We propose general parallel DP algorithms for pipeline and ring networks. The study of the optimality of these algorithms leads us to the introduction of new classes of multistage automata. However, the important class of Polyadic Dynamic Problems is out of the scope of this theory. Based on the concept of tree automaton, a new theory covering both Sequential and Parallel Dynamic Programming Polyadic Programs is presented. Monadic Programs appear as a particular case of this new theory. A large number of experiments have proved that the schemes proposed in this work lead to efficient implementations.

State-space support for path-based reward variables

Many sophisticated formalisms exist for specifying complex system behaviors, but methods for specifying performance and dependability variables have remained quite primitive. To cope with this problem, modelers often must augment system models with extra state information and event types to support particular variables. This often leads to models that are non-intuitive, and must be changed to support different variables. To address this problem, we extend the array of performance measures that may be derived from a given system model, by developing new performance measure specification and model construction techniques. Specifically, we introduce a class of path-based reward variables, and show how various performance measures may be specified using these variables. Path-based reward variables extend the previous work with reward structures to allow rewards to be accumulated based on sequences of states and transitions. To maintain the relevant history, we introduce the concept of a path automaton, whose state transitions are based on the system model state and transitions. Furthermore, we present a new procedure for constructing state spaces and the associated transition rate matrices that support path-based reward variables. Our new procedure takes advantage of the path automaton to allow a single system model to be used as the basis of multiple performance measures that would otherwise require separate models or a single more complicated model.

Discrete-event dynamic systems

The supervisory control theory of discrete-event dynamic systems (DEDS), first introduced by Ramadge and Wonham, is based on an automata concept. Given a process, the objective of this theory is to design a supervisor in such a way that the process coupled with the supervisor behaves according to various constraints. In this framework, the process is assumed to evolve spontaneously and the supervisor can only prevent some events from occurring, but cannot force them. In fact, most processes require the addition of an external control agent that forces some events to occur. This has led us to the supervised control concept where control and supervision are separated. This provides a hierarchical frame, thus enabling us to formalize and to systematize the transition from the synthesis to the implementation of the control. In the paper, Grafcet is intensively used for the supervision and the control design.

John von Neumann: the founding father of artificial life.

Aside from being known for his contributions to mathematics and physics, John von Neumann is considered one of the founding fathers of computer science and engineering. Not only did he do pioneering work on sequential computing systems, but he also carried out a major investigation of parallel architectures, leading to his work on cellular automata. His exceptional vision and daring, borrowing from biology the concept of genomic information even before the discovery of DNA's double helix, led him to propose the concept of self-reproducing automata.

A DTCNN universal machine based on highly parallel 2-D cellular automata CAM/sup 2/

The discrete-time cellular neural network (DTCNN) is a promising computer paradigm that fuses artificial neural networks with the concept of cellular automaton (CA) and has many applications to pixel-level image processing. Although some architectures have been proposed for processing DTCNN, there are no compact, practical computers that can process real-world images of several hundred thousand pixels at video rates. So, in spite of its great potential, DTCNNs are not being used for image processing outside the laboratory. This paper proposes a DTCNN processing method based on a highly parallel two-dimensional (2-D) cellular automata called CAM/sup 2/. CAM/sup 2/ can attain pixel-order parallelism on a single PC board because it is composed of a content addressable memory (CAM), which makes it possible to embed enormous numbers of processing elements, corresponding to CA cells, onto one VLSI chip. A new mapping method utilizes maskable search and parallel and partial write commands of CAM/sup 2/ to enable high-performance DTCNN processing. Evaluation results show that, on average, CAM/sup 2/ can perform one transition for various DTCNN templates in about 12 microseconds. Also it can perform practical image processing through a combination of DTCNNs and other CA-based algorithms. CAM/sup 2/ is a promising platform for processing DTCNN.