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Time Out of Joint: Attractors in Asynchronous Random Boolean Networks
 Proceedings of the Fourth European Conference on Artificial Life (ECAL97
, 1997
"... Random Boolean networks (RBNs) are complex systems composed of many simple components which have been much analysed and shown to have many robust generic properties. Some synchronous versions have been influential as highly abstract models of specific biological systems, but for many biological phen ..."
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Random Boolean networks (RBNs) are complex systems composed of many simple components which have been much analysed and shown to have many robust generic properties. Some synchronous versions have been influential as highly abstract models of specific biological systems, but for many biological phenomena asynchronous versions are more plausible models. Though asynchronous RBNs are indeterministic they can be shown to have generic properties that are simpler than, and very different from, the synchronous versions. These properties are demonstrated for the first time here through computer simulation and through analysis. 1 Introduction Models of complex physical and biological phenomena inevitably ignore much of the detail of the real phenomena and simplify into systems with a small number of concepts. Complex behaviour can be generated from conceptually simple primitive elements if they interconnect and interact in large numbers. Cellular automata (CAs) and Random Boolean Networks (RB...
Selection intensity in asynchronous cellular evolutionary algorithms
 Proceedings of the genetic and evolutionary computation conference GECCO’03
, 2003
"... Abstract. This paper presents a theoretical study of the selection pressure in asynchronous cellular evolutionary algorithms (cEAs). This work is motivated by the search for a general model for asynchronous update of the individuals in a cellular EA, and by the necessity of better accuracy beyond wh ..."
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Abstract. This paper presents a theoretical study of the selection pressure in asynchronous cellular evolutionary algorithms (cEAs). This work is motivated by the search for a general model for asynchronous update of the individuals in a cellular EA, and by the necessity of better accuracy beyond what existing models of selection intensity can provide. Therefore, we investigate the differences between the expected and actual values of the selection pressure induced by several asynchronous update policies, and formally characterize the update dynamics of each variant of the algorithm. New models for these two issues are proposed, and are shown to be more accurate (lower fit error) than previous ones. 1
Comparing synchronous and asynchronous cellular genetic algorithms
 Parallel Problem Solving from Nature  PPSN VII, volume 2439 of Lecture Notes in Computer Science
, 2002
"... Abstract. This paper presents a comparative study of several asynchronous policies for updating the population in a cellular genetic algorithm (cGA). Cellular GA’s are regular GA’s with the important exception that individuals are placed in a given geographical distribution (usually a 2d grid). ..."
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Abstract. This paper presents a comparative study of several asynchronous policies for updating the population in a cellular genetic algorithm (cGA). Cellular GA’s are regular GA’s with the important exception that individuals are placed in a given geographical distribution (usually a 2d grid). Operators are applied locally on a set made of each individual and the surrounding neighbors, thus promoting intraneighborhood exploitation and interneighborhood exploration of the search space. Here, we analyze the respective advantages and drawbacks of dealing with this decentralized population in the traditional synchronous manner or in several possible asynchronous update policies. Asynchronous behavior has proven to be better in many domains such as cellular automata and distributed GA’s, which, in turn, is also the main conclusion of this work. We will undergo a structured analysis on a set of problems with different features in order to get well grounded conclusions. 1
Indexed bibliography of distributed genetic algorithms
 University of Vaasa, Department of
, 1995
"... ..."
Decentralized cellular evolutionary algorithms
 Handbook of Bioinspired Algorithms and Applications, volume 7 of Chapman and HallCRC Computer and Information Science Series
, 2005
"... In this chapter we study cellular evolutionary algorithms, a kind of decentralized heuristics, and the importance of their induced exploration/exploitation balance on different problems. It is shown that, by choosing synchronous or asynchronous update policies, the selection pressure, and thus the e ..."
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In this chapter we study cellular evolutionary algorithms, a kind of decentralized heuristics, and the importance of their induced exploration/exploitation balance on different problems. It is shown that, by choosing synchronous or asynchronous update policies, the selection pressure, and thus the exploration/exploitation tradeoff, can be influenced directly, without using additional ad hoc parameters. The same effect can be obtained by using synchronous algorithms of different neighborhoodtotopology ratio. All the discussed algorithms are applied to a set of benchmark problems. Our conclusions show that the update methods of the asynchronous versions, as well as the ratio of the decentralized algorithm, have a marked influence on the efficiency and accuracy of the resulting algorithm. 1
Ordered asynchronous processes in natural and artificial systems
 Zealand: The University of Otago
, 2001
"... Models of multiagent systems with fixed network structure usually update the states of all agents in synchronous fashion. Examples include Cellular Automata, Random Boolean Networks and Artificial Neural Networks. Some recent studies have shown that the behaviour of such models can change dramatica ..."
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Models of multiagent systems with fixed network structure usually update the states of all agents in synchronous fashion. Examples include Cellular Automata, Random Boolean Networks and Artificial Neural Networks. Some recent studies have shown that the behaviour of such models can change dramatically if random asynchronous updating is used. Here we show that many real systems, both natural and artificial, undergo updating that is asynchronous, but ordered in some way. We use examples to demonstrate some of the properties of ordered asynchronous updating in Lsystems and cellular automata. In many cases, models of such processes effectively hide both their asynchronous nature, and the ordering, by embedding them in the model's details. This practice has prevented earlier recognition of ordered asynchronicity as well as some important implications. Among these implications are its role in the rise of modularity within complex systems. As an example, we introduce the “spotlight model ” of gene regulation, a random Boolean network in which controller nodes create modules by unfreezing different sets of nodes in turn. We argue that such models are not only more realistic representations of nature, but have potential advantages for solving complex problems.
Asynchronous Embryonics
 PROCEEDINGS OF 3 RD NASA/DOD WORKSHOP ON EVOLVABLE HARDWARE
, 2001
"... As embryonic arrays take inspiration from nature they display biological properties, namely complex structure and faulttolerance. However, they have yet to take advantage of a further biological feature at a fundamental level; asynchronous operation. In addition to the benefits normally associated ..."
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As embryonic arrays take inspiration from nature they display biological properties, namely complex structure and faulttolerance. However, they have yet to take advantage of a further biological feature at a fundamental level; asynchronous operation. In addition to the benefits normally associated with asynchronous digital design, such as intrinsic power management, two areas in which embryonic arrays could benefit are scalability and reliability. This paper gives an overview of embryonic systems and a pertinent asynchronous methodology, that of macromodules. It is shown that a macromodule approach allows the implementation of asynchronous circuits on Xilinx Virtex FPGAs using only the standard design tools. A preliminary VHDL simulation illustrates the operation of an asynchronous embryonic array. Although mentioned, little detail of the reconfiguration scheme is given for brevity. This simulation brings truly asynchronous embryonic circuits a step closer.
On Dynamical Genetic Programming: Random Boolean Networks in Learning Classifier Systems
, 2008
"... Abstract. Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system and yet dynamical representations remai ..."
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Abstract. Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system and yet dynamical representations remain almost unexplored within genetic programming. This paper presents results from an initial investigation into using a simple dynamical genetic programming representation within a Learning Classifier System. It is shown possible to evolve ensembles of dynamical Boolean function networks to solve versions of the wellknown multiplexer problem. Both synchronous and asynchronous systems are considered. 1.
On Dynamical Genetic Programming: Simple Boolean Networks in Learning Classifier Systems
, 2008
"... Abstract. Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system and yet dynamical representations remai ..."
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Cited by 3 (2 self)
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Abstract. Many representations have been presented to enable the effective evolution of computer programs. Turing was perhaps the first to present a general scheme by which to achieve this end. Significantly, Turing proposed a form of discrete dynamical system and yet dynamical representations remain almost unexplored within conventional genetic programming. This paper presents results from an initial investigation into using simple dynamical genetic programming representations within a Learning Classifier System. It is shown possible to evolve ensembles of dynamical Boolean function networks to solve versions of the wellknown multiplexer problem. Both synchronous and asynchronous systems are considered.
Reservoir Computing using Cellular Automata
"... We introduce a novel framework of reservoir computing. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application of a rule in the automaton for a per ..."
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We introduce a novel framework of reservoir computing. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a spacetime volume of the automaton state space, and it is used as the reservoir. The proposed framework is capable of long shortterm memory and it requires orders of magnitude less computation compared to Echo State Networks. Also, for additive cellular automaton rules, reservoir features can be combined using Boolean operations, which provides a direct way for concept building and symbolic processing, and it is much more efficient compared to stateoftheart approaches. 1