An AM Radio Receiver Designed With a Genetic Algorithm Based on a Bacterial Conjugation Genetic Operator

Perales-Gravan, Carlos; Lahoz-Beltrá, Rafael

doi:10.1109/tevc.2007.895271

Cited by 30 publications

(24 citation statements)

References 20 publications

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“…This aspect has been investigated in more detail for its possible applications on evolutionary optimization algorithms (Forrest, 1993;Goldberg, 1989;Perales-Gravan and Lahoz-Beltra, 2008). However, the quasispecies obtained in this kind of dynamic landscapes are not longer stable.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary Daisyworld models: A new approach to studying complex adaptive systems

Nuño

Vicente

Olarrea

et al. 2010

Ecological Informatics

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Keywords: Mathematical modelling Complex adaptive system Evolutionary algorithm Daisyworld CmasispeciesThis paper presents a model of a population of error-prone self-replicative species (replicators) that interact with its environment. The population evolves by natural selection in an environment whose change is caused by the evolutionary process itself. For simplicity, the environment is described by a single scalar factor, i.e. its temperature. The formal formulation of the model extends two basic models of Ecology and Evolutionary Biology, namely, Daisyworld and Quasispecies models. It is also assumed that the environment can also change due to external perturbations that are summed up as an external noise. Unlike previous models, the population size self-regulates, so no ad hoc population constraints are involved. When species replication is error-free, i.e. without mutation, the system dynamics can be described by an (n + l)-dimensional system of differential equations, one for each of the species initially present in the system, and another for the evolution of the environment temperature. Analytical results can be obtained straightforwardly in lowdimensional cases. In these examples, we show the stabilizing effect of thermal white noise on the system behavior. The error-prone self-replication, i.e. with mutation, is studied computationally. We assume that species can mutate two independent parameters: its optimal growth temperature and its influence on the environment temperature. For different mutation rates the system exhibits a large variety of behaviors. In particular, we show that a quasispecies distribution with an internal sub-distribution appears, facilitating species adaptation to new environments. Finally, this ecologically inspired evolutionary model is applied to study the origin and evolution of public opinion.

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Section: Discussionmentioning

confidence: 99%

Evolutionary Daisyworld models: A new approach to studying complex adaptive systems

Nuño

Vicente

Olarrea

et al. 2010

Ecological Informatics

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“…Bacterial conjugation is the transfer of a part of a plasmid (genetic material) from a donor bacterium to a recipient bacterium via a direct physical contact and is often regarded as sexual reproduction or mating between bacteria. Some researchers view the bacterial conjugation as a message exchange mechanism [4,37] .…”

Section: Conjugationmentioning

confidence: 99%

Bacterial foraging optimization using novel chemotaxis and conjugation strategies

Yang

Liu

et al. 2016

Information Sciences

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“…Our operator which includes the recombination between bacterial chromosomes assumes that donor bacterium is always Hfr. Two different conjugation operator versions (Perales-Graván and Lahoz-Beltra, 2008) have been defined (Figure 6). In both definitions since transfer of the donor bacterial chromosome is almost never complete, then the length of the strand transferred to the recipient cell has been simulated applying Monte Carlo's method and assuming DNA lengths exponentially distributed:

l = - \frac{1}{α} \ln (U)

being U a random number and α the conjugation parameter.…”

Section: Bacterial Evolutionmentioning

confidence: 99%

Bacterial computing: a form of natural computing and its applications

Lahoz-Beltrá¹,

Navarro²,

Marijuán³

2014

Front. Microbiol.

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The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular “learning” along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the possible application of both kinds of mechanisms to prokaryotic molecular computing schemes as well as to the solution of real world problems.

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An AM Radio Receiver Designed With a Genetic Algorithm Based on a Bacterial Conjugation Genetic Operator

Cited by 30 publications

References 20 publications

Evolutionary Daisyworld models: A new approach to studying complex adaptive systems

Evolutionary Daisyworld models: A new approach to studying complex adaptive systems

Bacterial foraging optimization using novel chemotaxis and conjugation strategies

Bacterial computing: a form of natural computing and its applications

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