Search

Background: The search for and rescue of missing persons is always coupled with a high demand on human resources. In cases of suspected drowning it is often necessary to search huge expanses of water. For depths of more than 3-5 m the search and rescue procedure needs to be performed by specialist rescue divers. Due to saturation with nitrogen caused by the higher ambient pressure during the dive, the operating time for each rescue diver is limited. In addition, each dive is linked with an increased risk., Objective: Miniaturization of sensors, higher performance of embedded systems and high energy density of modern accumulators offer the chance to operate with unmanned flying and diving vehicles for search and rescue even with moderate financial investment., Material and Methods: Based on funding by the Federation of the German Live Saving Association (DLRG) the DLRG national association of Bavaria procured three different models of remotely operated underwater vehicles (ROUV) and two different systems for underwater positioning. These systems will be offered to local associations of the DLRG in Bavaria for intense testing in their waters based on a common implementation strategy to ensure comparability and reproducibility., Results: Initial tests with different types of ROUV and underwater positioning have been performed in preparation of the survey. As a result, mini-ROUVs found in the lower consumer segment have been identified as insufficient as they are not able to carry the additional payload of the underwater positioning systems whilst maintaining controllability. In contrast, more complex drones are difficult to handle and require longer preparation times before they are ready for use. The ROUVs in the median range, preferably with a streamlined structure, have so far been found to be optimal; however, operating the vehicle without a positioning system is not recommended., Conclusion: In combination with an underwater positioning system, remotely operated underwater vehicles are identified as a reasonable supplement for rescue divers. Fast time to operation enables a preview of the operating area before starting the rescue operation and can therefore support the rescue diver team., (© 2021. Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

A novel evolutionary method that allows us to study the emergence of modularity for genotype-phenotype mapping in the course of Darwinian evolution is described. The method is based on composite epigenotypes with two parts: a binary genotype; and a mapping of genes onto phenotype characters. For such generalized epigenotypes the modularity is determined in the following intuitive way: The genes are divided into two subgroups; simultaneously with this decomposition there is defined an accompanying decomposition of the set of phenotype characters. We expect that for epigenotypes with modular structures the genes from one group will be mapped onto characters from the same group, that is, that the appearance of crosslink mappings will be maximally suppressed. A fundamental question for all of evolutionary biology (and also for evolutionary algorithms and connectionist cognitive science) is the mechanism of evolutionary emergence of modular structures. The presented explanatory model is an implementation of the assumption that variation in genotype is produced on a faster time scale than variation in the genotype-phenotype mapped part. Moreover, the evaluation of the epigenotype in the evolutionary algorithm is based on directly selectable properties (corresponding to the decomposition of the set of phenotype characters). The modularity of genotype-phenotype mapping emerges in the simulations.

The purpose of this article is to demonstrate that coordinated communication spontaneously emerges in a population composed of agents that are capable of specific cognitive activities. Internal states of agents are characterized by meaning vectors. Simple neural networks composed of one layer of hidden neurons perform cognitive activities of agents. An elementary communication act consists of the following: (a) two agents are selected, where one of them is declared the speaker and the other the listener; (b) the speaker codes a selected meaning vector onto a sequence of symbols and sends it to the listener as a message; and finally, (c) the listener decodes this message into a meaning vector and adapts his or her neural network such that the differences between speaker and listener meaning vectors are decreased. A Darwinian evolution enlarged by ideas from the Baldwin effect and Dawkins' memes is simulated by a simple version of an evolutionary algorithm without crossover. The agent fitness is determined by success of the mutual pairwise communications. It is demonstrated that agents in the course of evolution gradually do a better job of decoding received messages (they are closer to meaning vectors of speakers) and all agents gradually start to use the same vocabulary for the common communication. Moreover, if agent meaning vectors contain regularities, then these regularities are manifested also in messages created by agent speakers, that is, similar parts of meaning vectors are coded by similar symbol substrings. This observation is considered a manifestation of the emergence of a grammar system in the common coordinated communication.