Tag: Natural Computing

Preface to the Special Issue Unconventional Computing 2008

Preface to the Special Issue Unconventional Computing 2008
Content Type Journal ArticleDOI 10.1007/s11047-010-9221-1Authors
Cristian S. Calude, University of Auckland, Auckland, New ZealandJosé Felix Costa, IST Technical University of Lisbon, Lisbo…

Preface to the Special Issue Unconventional Computing 2008

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9221-1
  • Authors
    • Cristian S. Calude, University of Auckland, Auckland, New Zealand
    • José Felix Costa, IST Technical University of Lisbon, Lisbon, Portugal

(Tissue) P systems working in the k-restricted minimally or maximally parallel transition mode

Abstract  We investigate variants of the maximally and the minimally parallel transition mode, i.e., we allow only a bounded number
of rules to be taken from every set of the partitioning of the whole set of rules. The 1-restricted minimally…

Abstract  

We investigate variants of the maximally and the minimally parallel transition mode, i.e., we allow only a bounded number
of rules to be taken from every set of the partitioning of the whole set of rules. The 1-restricted minimally parallel transition
mode especially fits to describe the way transitions take place in spiking neural P systems without delays, i.e., in every
neuron where a rule is applicable exactly one rule has to be applied. Moreover, purely catalytic P systems working in the
maximally parallel transition mode can be described as P systems using the corresponding rules without catalysts, i.e., noncooperative
rules, when working in the 1-restricted minimally parallel transition mode. In contrast to these results for computationally
complete models of P systems, with the k-restricted maximally parallel transition mode noncooperative rules only allow for the generation of semi-linear sets.

  • Content Type Journal Article
  • Pages 821-833
  • DOI 10.1007/s11047-010-9215-z
  • Authors
    • Rudolf Freund, Faculty of Informatics, Vienna University of Technology, Favoritenstr. 9, 1040 Vienna, Austria
    • Sergey Verlan, LACL, Département Informatique, UFR Sciences et Technologie, Université Paris XII, 61, av. Général de Gaulle, 94010 Créteil, France

Introduction to special issue on Optical SuperComputing

Introduction to special issue on Optical SuperComputing
Content Type Journal ArticleDOI 10.1007/s11047-010-9220-2Authors
Shlomi Dolev, Ben-Gurion University of the Negev, Beersheba, IsraelTobias Haist, Stuttgart Universität, Stuttgart, GermanyMihai…

Introduction to special issue on Optical SuperComputing

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9220-2
  • Authors
    • Shlomi Dolev, Ben-Gurion University of the Negev, Beersheba, Israel
    • Tobias Haist, Stuttgart Universität, Stuttgart, Germany
    • Mihai Oltean, Babeş-Bolyai University, Cluj-Napoca, Romania

Priming: making the reaction to intrusion or fault predictable

Abstract  We propose and evaluate an immuno-inspired approach for misbehavior detection in ad hoc wireless networks. Misbehavior is
the result of an intrusion, or a software or hardware failure. Our misbehavior detection approach is inspired…

Abstract  

We propose and evaluate an immuno-inspired approach for misbehavior detection in ad hoc wireless networks. Misbehavior is
the result of an intrusion, or a software or hardware failure. Our misbehavior detection approach is inspired by the role
of co-stimulation and priming in the biological immune system (BIS). We translate priming into a computational paradigm that
can increase robustness as well as stimulate energy efficiency of misbehavior detection. We provide a detailed energy consumption
analysis with respect to the IEEE 802.11 and IEEE 802.15.4 protocols. We analyze the efficiency of misbehavior detection with
co-stimulation and priming. This analysis is complemented with experimental results. We show that co-stimulation and priming
introduce new options such as the ability to choose a trade-off between detection performance and energy efficiency. We provide
a summary of the challenges related to the design of co-stimulation and priming based architectures. We argue that co-stimulation
and priming are rather general paradigms with possible applications in other areas than misbehavior detection.

  • Content Type Journal Article
  • Pages 243-274
  • DOI 10.1007/s11047-010-9219-8
  • Authors
    • Martin Drozda, Simulation and Modeling Group, Faculty of Electrical Engineering and Computer Science, Leibniz University of Hannover, Welfengarten 1, 30167 Hannover, Germany
    • Sven Schaust, Simulation and Modeling Group, Faculty of Electrical Engineering and Computer Science, Leibniz University of Hannover, Welfengarten 1, 30167 Hannover, Germany
    • Sebastian Schildt, Institute of Operating Systems and Computer Networks, Technische Universität Braunschweig, Mühlenpfordtstr. 23, 38106 Braunschweig, Germany
    • Helena Szczerbicka, Simulation and Modeling Group, Faculty of Electrical Engineering and Computer Science, Leibniz University of Hannover, Welfengarten 1, 30167 Hannover, Germany

Self-assembly of decidable sets

Abstract  The theme of this paper is computation in Winfree’s Abstract Tile Assembly Model (TAM). We first review a simple, well-known
tile assembly system (the “wedge construction”) that is capable of universal computation. We then ex…

Abstract  

The theme of this paper is computation in Winfree’s Abstract Tile Assembly Model (TAM). We first review a simple, well-known
tile assembly system (the “wedge construction”) that is capable of universal computation. We then extend the wedge construction
to prove the following result: if a set of natural numbers is decidable, then it and its complement’s canonical two-dimensional
representation self-assemble. This leads to a novel characterization of decidable sets of natural numbers in terms of self-assembly.
Finally, we show that our characterization is robust with respect to various (restrictive) geometrical constraints.

  • Content Type Journal Article
  • Pages 853-877
  • DOI 10.1007/s11047-010-9218-9
  • Authors
    • Matthew J. Patitz, Department of Computer Science, University of Texas–Pan American, Edinburg, TX 78539, USA
    • Scott M. Summers, Department of Computer Science and Software Engineering, University of Wisconsin–Platteville, Platteville, WI 53818, USA

On the verification of membrane systems with dynamic structure

Abstract  We study computational properties of Gheorge Păun’s P-systems extended with rules that model in an abstract way creation,
dissolution, fusion and cloning of membranes. We investigate decision problems like reachability of a conf…

Abstract  

We study computational properties of Gheorge Păun’s P-systems extended with rules that model in an abstract way creation,
dissolution, fusion and cloning of membranes. We investigate decision problems like reachability of a configuration, boundedness
(finiteness of the state space), and coverability (verification of safety properties). Our analysis is aimed at understanding
the expressive power of rules that dynamically modify the structure of a membrane.

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9214-0
  • Authors
    • Giorgio Delzanno, Università di Genova, Genova, Italy
    • Laurent Van Begin, Université Libre de Bruxelles, Brussels, Belgium

On the verification of membrane systems with dynamic structure

Abstract  We study computational properties of Gheorge Păun’s P-systems extended with rules that model in an abstract way creation,
dissolution, fusion and cloning of membranes. We investigate decision problems like reachability of a conf…

Abstract  

We study computational properties of Gheorge Păun’s P-systems extended with rules that model in an abstract way creation,
dissolution, fusion and cloning of membranes. We investigate decision problems like reachability of a configuration, boundedness
(finiteness of the state space), and coverability (verification of safety properties). Our analysis is aimed at understanding
the expressive power of rules that dynamically modify the structure of a membrane.

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9214-0
  • Authors
    • Giorgio Delzanno, Università di Genova, Genova, Italy
    • Laurent Van Begin, Université Libre de Bruxelles, Brussels, Belgium

Grammar-based immune programming

Abstract  This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological
inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and…

Abstract  

This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological
inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and decode candidate
solutions to a valid representation (program). However, by default, GE uses a Genetic Algorithm in the search process while
GIP uses an artificial immune system. Some modifications are needed of an immune algorithm to use a grammar in order to efficiently
decode antibodies into programs. Experiments are performed to analyze algorithm behavior over different aspects and compare
it with GEVA, a well known GE implementation. The methods are applied to identify a causal model (an ordinary differential
equation) from an observed data set, to symbolically regress an iterated function f(f(x)) = g(x), and to find a symbolic representation of a discontinuous function.

  • Content Type Journal Article
  • DOI 10.1007/s11047-010-9217-x
  • Authors
    • Heder S. Bernardino, Laboratório Nacional de Computação Científica, Av. Getulio Vargas, 333, 25.651-075 Petrópolis, RJ Brazil
    • Helio J. C. Barbosa, Laboratório Nacional de Computação Científica, Av. Getulio Vargas, 333, 25.651-075 Petrópolis, RJ Brazil

Grammar-based immune programming

Abstract  This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological
inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and…

Abstract  

This paper describes Grammar-based Immune Programming (GIP) for evolving programs in an arbitrary language by immunological
inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and decode candidate
solutions to a valid representation (program). However, by default, GE uses a Genetic Algorithm in the search process while
GIP uses an artificial immune system. Some modifications are needed of an immune algorithm to use a grammar in order to efficiently
decode antibodies into programs. Experiments are performed to analyze algorithm behavior over different aspects and compare
it with GEVA, a well known GE implementation. The methods are applied to identify a causal model (an ordinary differential
equation) from an observed data set, to symbolically regress an iterated function f(f(x)) = g(x), and to find a symbolic representation of a discontinuous function.

  • Content Type Journal Article
  • Pages 209-241
  • DOI 10.1007/s11047-010-9217-x
  • Authors
    • Heder S. Bernardino, Laboratório Nacional de Computação Científica, Av. Getulio Vargas, 333, 25.651-075 Petrópolis, RJ Brazil
    • Helio J. C. Barbosa, Laboratório Nacional de Computação Científica, Av. Getulio Vargas, 333, 25.651-075 Petrópolis, RJ Brazil

A simple mass-action model for the eukaryotic heat shock response and its mathematical validation

Abstract  The heat shock response is a primordial defense mechanism against cell stress and protein misfolding. It proceeds with the
minimum number of mechanisms that any regulatory network must include, a stress-induced activation and a fee…

Abstract  

The heat shock response is a primordial defense mechanism against cell stress and protein misfolding. It proceeds with the
minimum number of mechanisms that any regulatory network must include, a stress-induced activation and a feedback regulation,
and can thus be regarded as the archetype for a cellular regulatory process. We propose here a simple mechanistic model for
the eukaryotic heat shock response, including its mathematical validation. Based on numerical predictions of the model and
on its sensitivity analysis, we minimize the model by identifying the reactions with marginal contribution to the heat shock
response. As the heat shock response is a very basic and conserved regulatory network, our analysis of the network provides
a useful foundation for modeling strategies of more complex cellular processes.

  • Content Type Journal Article
  • Pages 595-612
  • DOI 10.1007/s11047-010-9216-y
  • Authors
    • Ion Petre, Department of Information Technologies, Åbo Akademi University, Turku, 20520 Finland
    • Andrzej Mizera, Department of Information Technologies, Åbo Akademi University, Turku, 20520 Finland
    • Claire L. Hyder, Turku Centre for Biotechnology, Turku, Finland
    • Annika Meinander, Turku Centre for Biotechnology, Turku, Finland
    • Andrey Mikhailov, Turku Centre for Biotechnology, Turku, Finland
    • Richard I. Morimoto, Department of Biochemistry, Molecular Biology and Cell Biology, Rice Institute for Biomedical Research, Northwestern University, Evanston, IL 60208, USA
    • Lea Sistonen, Turku Centre for Biotechnology, Turku, Finland
    • John E. Eriksson, Turku Centre for Biotechnology, Turku, Finland
    • Ralph-Johan Back, Department of Information Technologies, Åbo Akademi University, Turku, 20520 Finland