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Biomedical subjects

W Banzhaf

Publications and source records attributed to W Banzhaf.

11 recordsLinked to original sources
PubMed2001

Evolving control metabolisms for a robot.

This article demonstrates a new method of programming artificial chemistries. It uses the emerging capabilities of the system's dynamics for information-processing purposes. By evolution of metabolisms that act as control programs for a small robot one achieves the adaptation of the internal metabolic pathways as well as the selection of the most relevant available exteroceptors. The underlying artificial chemistry evolves efficient information-processing pathways with most benefit for the desired task, robot navigation. The results show certain relations to such biological systems as motile bacteria.

Metabolism↗
PubMed2001

Artificial chemistries--a review.

This article reviews the growing body of scientific work in artificial chemistry. First, common motivations and fundamental concepts are introduced. Second, current research activities are discussed along three application dimensions: modeling, information processing, and optimization. Finally, common phenomena among the different systems are summarized. It is argued here that artificial chemistries are "the right stuff" for the study of prebiotic and biochemical evolution, and they provide a productive framework for questions regarding the origin and evolution of organizations in general. Furthermore, artificial chemistries have a broad application range of practical problems, as shown in this review.

Chemistry↗
PubMed2000

Spontaneous group formation in the seceder model.

The seceder model shows how the local tendency to be different gives rise to the formation of groups. The model consists of a population of simple entities which reproduce and die. In a single reproduction event three individuals are chosen randomly and the individual which possesses the largest distance to their center is reproduced by creating a mutated offspring. The offspring replaces a randomly chosen individual of the population. The paper demonstrates the complex group formation behavior and its dependency on the population size.

Computer Simulation↗
PubMed2000

Cryptography with DNA binary strands.

Biotechnological methods can be used for cryptography. Here two different cryptographic approaches based on DNA binary strands are shown. The first approach shows how DNA binary strands can be used for steganography, a technique of encryption by information hiding, to provide rapid encryption and decryption. It is shown that DNA steganography based on DNA binary strands is secure under the assumption that an interceptor has the same technological capabilities as sender and receiver of encrypted messages. The second approach shown here is based on steganography and a method of graphical subtraction of binary gel-images. It can be used to constitute a molecular checksum and can be combined with the first approach to support encryption. DNA cryptography might become of practical relevance in the context of labelling organic and inorganic materials with DNA 'barcodes'.

Computer Communication Networks↗
PubMed1998

Self-evolution in a constructive binary string system.

We examine the qualitative dynamics of a catalytic self-organizing system of binary strings that is inspired by the chemical information processing metaphor. A string is interpreted in two different ways: either (a) as raw data or (b) as a machine that is able to process another string as data in order to produce a third one. This article focuses on the phenomena of evolution whose appearance is notable because no explicit mutation, recombination, or artificial selection operators are introduced. We call the system self-evolving because every variation is performed by the objects themselves in their machine form.

Artificial Intelligence↗
PubMed1989

Population processing--a powerful class of parallel algorithms.

We present a model of optimization of cost functions by a population of parallel processors and argue that especially diploid recombination of gene strings is a promising recipe for optimization which nature proliferates. Based on a simulated evolutionary search strategy diploidy is introduced as a means for maintaining variability in computational problems with large numbers of local extrema. A differentiation into genotypes and phenotypes is performed. The applied strategy is compared to some traditional algorithms simulating evolution on the basis of two sample cost functions.

Algorithms↗