Showing papers in "Natural Computing in 2007"
TL;DR: This paper aims to offer a compendious and timely review of the field and the challenges and opportunities offered by this welcome addition to the optimization toolbox.
Abstract: Particle Swarm Optimization (PSO), in its present form, has been in existence for roughly a decade, with formative research in related domains (such as social modelling, computer graphics, simulation and animation of natural swarms or flocks) for some years before that; a relatively short time compared with some of the other natural computing paradigms such as artificial neural networks and evolutionary computation. However, in that short period, PSO has gained widespread appeal amongst researchers and has been shown to offer good performance in a variety of application domains, with potential for hybridisation and specialisation, and demonstration of some interesting emergent behaviour. This paper aims to offer a compendious and timely review of the field and the challenges and opportunities offered by this welcome addition to the optimization toolbox. Part I discusses the location of PSO within the broader domain of natural computing, considers the development of the algorithm, and refinements introduced to prevent swarm stagnation and tackle dynamic environments. Part II considers current research in hybridisation, combinatorial problems, multicriteria and constrained optimization, and a range of indicative application areas.
585 citations
TL;DR: This work provides an introduction and analysis of the key developments within the use of artificial immune systems in intrusion detection, in addition to making suggestions for future research.
Abstract: The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. First, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Second, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.
349 citations
TL;DR: It is argued that the field of artificial immune systems (AIS) has reached an impasse, and a number of challenges to the AIS community can be undertaken to help move the area forward.
Abstract: In this position paper, we argue that the field of artificial immune systems (AIS) has reached an impasse. For many years, immune inspired algorithms, whilst having some degree of success, have been limited by the lack of theoretical advances, the adoption of a naive immune inspired approach and the limited application of AIS to challenging problems. We review the current state of the AIS approach, and suggest a number of challenges to the AIS community that can be undertaken to help move the area forward.
161 citations
TL;DR: This work presents a novel method for extraction of spike features based on a combination of PCA and continuous WT, and shows that only when properly tuned to the data, the WT technique may outperform PCA.
Abstract: Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is defined by the quality of discriminative features extracted from spike waveforms. Here we discuss two features extraction approaches: principal component analysis (PCA), and wavelet transform (WT). We show that only when properly tuned to the data, the WT technique may outperform PCA. We present a novel method for extraction of spike features based on a combination of PCA and continuous WT. The method automatically tunes its WT part to the data structure making use of knowledge obtained by PCA. We demonstrate the method on simulated and experimental data sets.
71 citations
TL;DR: It is shown that latching dynamics can span the range from deterministic to random under the control of a threshold parameter U, and how finite latching sequences can become infinite, depending on the properties of the transition probability matrix and of its eigenvalues.
Abstract: We study latching dynamics, i.e. the ability of a network to hop spontaneously from one discrete attractor state to another, which has been proposed as a model of an infinitely recursive process in large scale cortical networks, perhaps associated with higher cortical functions, such as language. We show that latching dynamics can span the range from deterministic to random under the control of a threshold parameter U. In particular, the interesting intermediate case is characterized by an asymmetric and complex set of transitions. We also indicate how finite latching sequences can become infinite, depending on the properties of the transition probability matrix and of its eigenvalues.
29 citations
TL;DR: The presented results demonstrate how extremely small reflex-oscillators, which inherently rely on the sensorimotor loop and e.g. hysteresis effects, generate effective locomotion.
Abstract: As a prerequisite for developing neural control for walking machines that are able to autonomously navigate through rough terrain, artificial structure evolution is used to generate various single leg controllers. The structure and dynamical properties of the evolved (recurrent) neural networks are then analysed to identify elementary mechanisms of sensor-driven walking behaviour. Based on the biological understanding that legged locomotion implies a highly decentralised and modular control, neuromodules for single, morphological distinct legs of a hexapod walking machine were developed by using a physical simulation. Each of the legs has three degrees of freedom (DOF). The presented results demonstrate how extremely small reflex-oscillators, which inherently rely on the sensorimotor loop and e.g. hysteresis effects, generate effective locomotion. Varying the fitness function by randomly changing the environmental conditions during evolution, neural control mechanisms are identified which allow for robust and adaptive locomotion. Relations to biological findings are discussed.
24 citations
TL;DR: It is proved that the compositional and the holistic semantics characterize the same logic.
Abstract: In quantum computational logic meanings of sentences are identified with quantum information quantities: systems of qubits or, more generally, mixtures of systems of qubits. We consider two kinds of quantum computational semantics: (1) a compositional semantics, where the meaning of a compound sentence is determined by the meanings of its parts; (2) a holistic semantics, which makes essential use of the characteristic "holistic" features of the quantum-theoretic formalism. We prove that the compositional and the holistic semantics characterize the same logic.
23 citations
TL;DR: This work starts from the hypothesis that it is useful to look at the neuronal circuits assuming that they are the neurophysiological support of a calculus, whose full description requires considering, at least, three levels of organization: circuits and mechanisms, neurophysiology symbols and knowledge and emerging behavior.
Abstract: Virtually from its origins, with Alan Turing and W.S. McCulloch's formulations, the use of the computational paradigm (CP) as a conceptual and theoretical framework to help to explain Neurophysiology and Cognition has aroused controversy. Some of the objections raised, relating to its constitutive and formal limitations, still prevail. We believe that others stem from the assumption that its objectives are different from those of a methodological approach to the problem of neural modeling.
In this work we start from the hypothesis that it is useful to look at the neuronal circuits assuming that they are the neurophysiological support of a calculus, whose full description requires considering, at least, three levels of organization: circuits and mechanisms, neurophysiological symbols and knowledge and emerging behavior. We also stress the figure of the external observer and the need to distinguish between two description domains in each level: the level's own domain and the domain of the external observer. Finally, we describe a procedure for using the computational paradigm qualitatively in order to try to do "reverse neurophysiology", drawing on two abstraction processes that link the calculus at signal level with cognition. We end by considering the real limitations (constitutive) and apparent (wrong objectives) of the CP and its integrating and non-exclusive nature.
12 citations
TL;DR: A computational model in programming environment TiViPE is constructed that closely resembles the functional behavior of the neuronal responses of non-orientation (within the CRF) sensitive 4Cβ cells and gives an explanation of the indirect information flow in V1 that explains the behavior of orientation contrast sensitivity.
Abstract: Many cells in the primary visual cortex respond differently when a stimulus is placed outside their classical receptive field (CRF) compared to the stimulus within the CRF alone, permitting integration of information at early levels in the visual processing stream that may play a key role in intermediate-level visual tasks, such a perceptual pop-out [Knierim JJ, van Essen DC (1992) J Neurophysiol 67(5):961---980; Nothdurft HC, Gallant JL, Essen DCV (1999) Visual Neurosci 16:15---34], contextual modulation [Levitt JB, Lund JS (1997) Nature 387:73---76; Das A, Gilbert CD (1999) Nature 399:655---661; Dragoi V, Sur M (2000) J Neurophysiol 83:1019---1030], and junction detection [Sillito AM, Grieve KL, Jones HE, Cudiero J, Davis J (1995) Nature 378:492---496; Das A, Gilbert CD (1999) Nature 399:655---661; Jones HE, Wang W, Sillito AM (2002) J Neurophysiol 88:2797---2808]. In this article, we construct a computational model in programming environment TiViPE [Lourens T (2004) TiViPE--Tino's visual programming environment. In: The 28th Annual International Computer Software & Applications Conference, IEEE COMPSAC 2004, pp 10---15] of orientation contrast type of cells and demonstrate that the model closely resembles the functional behavior of the neuronal responses of non-orientation (within the CRF) sensitive 4Cβ cells [Jones HE, Wang W, Sillito AM (2002) J Neurophysiol 88:2797---2808], and give an explanation of the indirect information flow in V1 that explains the behavior of orientation contrast sensitivity. The computational model of orientation contrast cells demonstrates excitatory responses at edges near junctions that might facilitate junction detection, but the model does not reveal perceptual pop-out.
11 citations
TL;DR: The experimental results show that such a multistage approach is a competitive and effective search method in the conformational search space of real proteins, in terms of solution quality and computational cost comparing the results of the current state-of-art algorithms.
Abstract: Natural proteins quickly fold into a complicated three-dimensional structure. Evolutionary algorithms have been used to predict the native structure with the lowest energy conformation of the primary sequence of a given protein. Successful structure prediction requires a free energy function sufficiently close to the true potential for the native state, as well as a method for exploring the conformational space. Protein structure prediction is a challenging problem because current potential functions have limited accuracy and the conformational space is vast. In this work, we show an innovative approach to the protein folding (PF) problem based on an hybrid Immune Algorithm (IMMALG) and a quasi-Newton method starting from a population of promising protein conformations created by the global optimizer DIRECT. The new method has been tested on Met-Enkephelin peptide, which is a paradigmatic example of multiple---minima problem, 1POLY, 1ROP and the three helix protein 1BDC. DIRECT produces an initial population of promising candidate solutions within a potentially optimal rectangle for the funnel landscape of the PF problem. Hence, IMMALG starts from a population of promising protein conformations created by the global optimizer DIRECT. The experimental results show that such a multistage approach is a competitive and effective search method in the conformational search space of real proteins, in terms of solution quality and computational cost comparing the results of the current state-of-art algorithms.
11 citations
Journal Article•
TL;DR: This work proposes using an adaptive importance sampling technique which allows us to actively control the trade-off between bias and variance, and provides a method for optimally determining theTrade-off parameter based on a variant of cross-validation.
TL;DR: How a Multi-Agent approach, and more precisely the situated cellular agents (SCA) model, can be applied to represent specific elements and mechanisms of the immune system is described.
Abstract: The immune system (IS) represents the defence mechanism of higher level organisms to micro organismic threats. It is a very complex system, genuinely distributed and providing mechanisms of adaptation to unknown threats by means of the interaction among the heterogenous autonomous entities it is composed of. The most relevant features of the overall system, such as learning capabilities and the possibility to tackle unknown threats in any part of the body, are a consequence of these interactions. This paper describes how a Multi-Agent approach, and more precisely the situated cellular agents (SCA) model, can be applied to represent specific elements and mechanisms of the IS. After a brief description of the IS, a brief overview of possible modelling approaches will be given, then the SCA model will be introduced and exploited to model some elements and mechanisms of the IS. This work is one of the results of an interdisciplinary research that has involved immunologists of the Advanced Biotechnology Center of Genova and computer scientists of the University of Milan-Bicocca.
TL;DR: In this paper, a quantum generalization of Brudno's result is discussed, which connects the von Neumann entropy rate and a recently proposed quantum algorithmic complexity, which is a quantum extension of the Brudnon theorem.
Abstract: A theorem of Brudno says that the entropy production of classical ergodic information sources equals the algorithmic complexity per symbol of almost every sequence emitted by such sources. The recent advances in the theory and technology of quantum information raise the question whether a same relation may hold for ergodic quantum sources. In this paper, we discuss a quantum generalization of Brudno's result which connects the von Neumann entropy rate and a recently proposed quantum algorithmic complexity.
TL;DR: This paper develops new unary operators on languages for characterizing bond-free properties exactly, using familiar code-theoretic equations and focuses on relationships to classes of languages from the theory of codes.
Abstract: The absence of the ability to form a specified set of bonds in a collection of DNA strands is crucial in the design of experiments encoding algorithmic problems as single- or double-stranded DNA. Recently, the specification of the bonding types to be avoided has been formalized by defining bond-free properties. Bond-free properties generalize several bonding properties which have been studied in the context of DNA computing. In this paper, we consider a bond-free property as defining a class of languages. We study the properties of these classes of languages. We develop new unary operators on languages for characterizing bond-free properties exactly, using familiar code-theoretic equations. These new operators provide a new characterization of maximal bond-free properties as well. We also focus on relationships to classes of languages from the theory of codes.
TL;DR: It is argued that the proposed model embodies a sort of unifying paradigm for computing inspired by Nature and, even more ambitiously, a universal setting in which suitably encoded quantum symbolic manipulations of combinatorial, topological and algebraic problems might find their ‘natural’ computational reference model.
Abstract: In the past few years there has been a tumultuous activity aimed at introducing novel conceptual schemes for quantum computing. The approach proposed in (Marzuoli and Rasetti, 2002, 2005a) relies on the (re)coupling theory of SU(2) angular momenta and can be viewed as a generalization to arbitrary values of the spin variables of the usual quantum-circuit model based on `qubits' and Boolean gates. Computational states belong to finite-dimensional Hilbert spaces labelled by both discrete and continuous parameters, and unitary gates may depend on quantum numbers ranging over finite sets of values as well as continuous (angular) variables. Such a framework is an ideal playground to discuss discrete (digital) and analogic computational processes, together with their relationships occurring when a consistent semiclassical limit takes place on discrete quantum gates. When working with purely discrete unitary gates, the simulator is naturally modelled as families of quantum finite states-machines which in turn represent discrete versions of topological quantum computation models. We argue that our model embodies a sort of unifying paradigm for computing inspired by Nature and, even more ambitiously, a universal setting in which suitably encoded quantum symbolic manipulations of combinatorial, topological and algebraic problems might find their `natural' computational reference model.
TL;DR: G Gödel’s perspective on mechanical computability as articulated in his [193?], where he drew a dramatic conclusion from the undecidability of certain Diophantine propositions, namely, that mathematicians cannot be replaced by machines, is discussed.
Abstract: Turing's notion of human computability is exactly right not only for obtaining a negative solution of Hilbert's Entscheidungsproblem that is conclusive, but also for achieving a precise characterization of formal systems that is needed for the general formulation of the incompleteness theorems. The broad intellectual context reaches back to Leibniz and requires a focus on mechanical procedures; these procedures are to be carried out by human computers without invoking higher cognitive capacities. The question whether there are strictly broader notions of effectiveness has of course been asked for both cognitive and physical processes. I address this question not in any general way, but rather by focusing on aspects of mathematical reasoning that transcend mechanical procedures.
Section 1 discusses Godel's perspective on mechanical computability as articulated in his [193?], where he drew a dramatic conclusion from the undecidability of certain Diophantine propositions, namely, that mathematicians cannot be replaced by machines. That theme is taken up in the Gibbs Lecture of 1951; Godel argues there in greater detail that the human mind infinitely surpasses the powers of any finite machine. An analysis of the argument is presented in Section 2 under the heading Beyond calculation. Section 3 is entitled Beyond discipline and gives Turing's view of intelligent machinery; it is devoted to the seemingly sharp conflict between Godel's and Turing's views on mind. Their deeper disagreement really concerns the nature of machines, and I'll end with some brief remarks on (supra-) mechanical devices in Section 4.
TL;DR: An aging mechanism which develops in artificial bacterial populations fighting against antibiotic molecules is proposed, which appears compliant with recent studies on the field, and physically feasible.
Abstract: We propose an aging mechanism which develops in artificial bacterial populations fighting against antibiotic molecules. The mechanism is based on very elementary information gathered by each individual and elementary reactions as well. Though we do not interpret the aging process in strictly biological terms, it appears compliant with recent studies on the field, and physically feasible. The root of the aging mechanism is an adaptation strategy based on a thresholding operation that derives from theoretical results on stochastic monotone games. The methods for implementing it denote their rationale in that they represent a sophisticated dialect of pi-calculus, a widespread computational paradigm for implementing dynamics of massive populations with bipolar reactions. As a result we may implement processes that explain some typical patterns of the evolution of the immunosystems.
TL;DR: A self-assembly algorithm for synchronising agents and have them arrange according to a particular graph is given, which relies only on point-to-point communication, and can deal with any assembly graph whereas Klavins’ method dealt only with trees.
Abstract: A self-assembly algorithm for synchronising agents and have them arrange according to a particular graph is given. This algorithm, expressed using an ad hoc rule-based process algebra, extends Klavins' original proposal (Klavin, 2002: Automatic synthesis of controllers for assembly and formation forming. In: Proceedings of the International Conference on Robotics and Automation), in that it relies only on point-to-point communication, and can deal with any assembly graph whereas Klavins' method dealt only with trees.
TL;DR: In this article, the authors explore the problem of designing the provably shortest genomic sequence to encode a given set of genes by exploiting alternate reading frames, and present an algorithm for designing the shortest DNA sequence simultaneously encoding two given amino acid sequences.
Abstract: The emerging field of synthetic biology moves beyond conventional genetic manipulation to construct novel life forms which do not originate in nature. We explore the problem of designing the provably shortest genomic sequence to encode a given set of genes by exploiting alternate reading frames. We present an algorithm for designing the shortest DNA sequence simultaneously encoding two given amino acid sequences. We show that the coding sequence of naturally occurring pairs of overlapping genes approach maximum compression. We also investigate the impact of alternate coding matrices on overlapping sequence design. Finally, we discuss an interesting application for overlapping gene design, namely the interleaving of an antibiotic resistance gene into a target gene inserted into a virus or plasmid for amplification.
TL;DR: An outline of the asymptotic behavior of FPT densities is provided, which is particularly useful to discuss neuronal firing under certain slow activity conditions, and any conclusion on this matter is strongly model-dependent.
Abstract: This work is a contribution towards the understanding of certain features of mathematical models of single neurons. Emphasis is set on neuronal firing, for which the first passage time (FPT) problem bears a fundamental relevance. We focus the attention on modeling the change of the neuron membrane potential between two consecutive spikes by Gaussian stochastic processes, both of Markov and of non-Markov types. Methods to solve the FPT problems, both of a theoretical and of a computational nature, are sketched, including the case of random initial values. Significant similarities or diversities between computational and theoretical results are pointed out, disclosing the role played by the correlation time that has been used to characterize the neuronal activity. It is highlighted that any conclusion on this matter is strongly model-dependent. In conclusion, an outline of the asymptotic behavior of FPT densities is provided, which is particularly useful to discuss neuronal firing under certain slow activity conditions.
TL;DR: It is demonstrated that a search for barriers in communications brings a lot of interesting and deep outcomes and that relations between information processing in the real and virtual worlds, or between physical and information worlds, are likely very deep and more complex than realized.
Abstract: Several new and broader views on computation in Nature and by Nature, and on its limitations and barriers are presented and analysed briefly. Quantum information precessing, global network information processing and cosmology-based information processing theories are seen as three extreme, but well-founded approaches to computation by Nature. It is also emphasized that a search for barriers and limitations in information processing as well as attempts to overcome their barriers or to shift limitations, can have deep impacts on science, especially if they are accompanied by a search for limitations and barriers also in communication and security. It is demonstrated that a search for barriers in communications brings a lot of interesting and deep outcomes.
Computational and communication complexity is shown to play an important role in evaluating various approaches to get through barriers that current physical theories impose. It is also argued that a search for barriers and limitations concerning feasibility in information processing and physical worlds are of equal or maybe even of larger importance than those to overcome the Church-Turing barrier and some communication barriers. It is also emphasized that relations between information processing in the real and virtual worlds, or between physical and information worlds, are likely very deep and more complex than realized. All that has even broader sense than usually realized because we are witnessing a radical shift in the main characterization of the current science in general. A shift from so called Galilean science dominated by mathematics, to the Informatics (based) science - an informatics methodology based science and technology.
TL;DR: The design of a novel, irreversible memory element for use in artificial DNA-based computing systems is presented and ‘wet-ware’ demonstrations of the validity of key assumptions of the design are provided.
Abstract: We present the design of a novel, irreversible memory element for use in artificial DNA-based computing systems and provide `wet-ware' demonstrations of the validity of key assumptions of our design. The mechanism makes use of a DNA switch with a rotatable mid-section that contains a bacterial promoter and non-rotatable end sections, each of which contains a gene encoding a different fluorescent protein. The state (orientation) of the rotatable mid-section is therefore reported by the fluorescent colour produced when the plasmid is in a system that permits transcription and translation. Rotation of the mid-section from the `unset' to the `set' state is achieved by digestion of specific sites on the switch by the asymmetric restriction enzyme, Bpu10I, followed by ligation. Once set, the rotatable section cannot be cut again by the enzyme, so that state is held irreversibly even when exposed again to the switching signal. This mechanism has potential applications for permanently recording, in DNA, the occurrence of transient events.
TL;DR: The results suggest that the role of CN could be to transform the stimulus representation in order to facilitate both discrimination and classification in later processing stages.
Abstract: This paper explores the information coding performed by the local circuit of the Cuneate Nucleus (CN). On the basis of physiological data, we have developed a realistic computational model and studied its output in response to different types of plausible cutaneous stimuli. Computer simulations show that (1) static stimuli are encoded in progressive spatio-temporal patterns made up of single-spike trains generated by each stimulated neuron, and (2) moving stimuli are encoded with a bursting discharge of those units responding to the leading edge of the stimulus. These results suggest that the role of CN could be to transform the stimulus representation in order to facilitate both discrimination and classification in later processing stages.