Co-evolution of morphology and control in developing structures

The continuous need to increase the efficiency of technical systems requires the utilization of complex adaptive systems which operate in environments which are not completely predictable. Reasons are often random nature of the environment and the fact that not all phenomena which influence the performance of the system can be explained in full detail. As a consequence, the developer often gets confronted with the task to design an adaptive system with the lack of prior knowledge about the problem at hand. The design of adaptive systems, which react autonomously to changes in their environment, requires the coordinated generation of sensors, providing information about the environment, actuators which change the current state of the system and signal processing structures thereby generating suitable reactions to changed conditions. Within the scope of the thesis, the new system growth method has been introduced. It is based on the evolutionary optimization design technique, which can automatically produce the efficient systems with optimal initially non-defined configuration. The final solutions produced by the novel growth method have low dimensional perception, actuation and signal processing structures optimally adjusted to each other during combined evolutionary optimization process. The co-evolutionary system design approach has been realized by the concurrent development and gradual complexification of the sensory, actuation and corresponding signal processing systems during entire optimization. The evolution of flexible system configuration is performed with the standard evolutionary strategies by means of adaptable representation of variable length and therewith variable complexity of the system which it can represent in the further optimization progress. The co-evolution of morphology and control of complex adaptive systems has been successfully performed for the examples of a complex aerodynamic problem of a morphing wing and a virtual intelligent autonomously driving vehicle. The thesis demonstrates the applicability of the concurrent evolutionary design of the optimal morphological configuration, presented as sensory and actuation systems, and the corresponding optimal system controller. Meanwhile, it underlines the potentials of direct genotype – phenotype encodings for the design of complex engineering real-world applications. The thesis argues that often better, cheaper, more robust and adaptive systems can be developed if the entire system is the design target rather than its separate functional parts, like sensors, actuators or controller structure. The simulation results demonstrate that co-evolutionary methods are able to generate systems which can optimally adapt to the unpredicted environmental conditions while at the same time shedding light on the precise synchronization of all functional system parts during its co-developmental process

Robot control with biological cells

At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robot’s actuators

Continued Neurogenesis in Adult Drosophila as a Mechanism for Recruiting Environmental Cue-Dependent Variants

Background The skills used by winged insects to explore their environment are strongly dependent upon the integration of neurosensory information comprising visual, acoustic and olfactory signals. The neuronal architecture of the wing contains a vast array of different sensors which might convey information to the brain in order to guide the trajectories during flight. In Drosophila, the wing sensory cells are either chemoreceptors or mechanoreceptors and some of these sensors have as yet unknown functions. The axons of these two functionally distinct types of neurons are entangled, generating a single nerve. This simple and accessible coincidental signaling circuitry in Drosophila constitutes an excellent model system to investigate the developmental variability in relation to natural behavioral polymorphisms. Methodology/Principal Findings A fluorescent marker was generated in neurons at all stages of the Drosophila life cycle using a highly efficient and controlled genetic recombination system that can be induced in dividing precursor cells (MARCM system, flybase web site). It allows fluorescent signals in axons only when the neuroblasts and/or neuronal cell precursors like SOP (sensory organ precursors) undergo division during the precedent steps. We first show that a robust neurogenesis continues in the wing after the adults emerge from the pupae followed by an extensive axonal growth. Arguments are presented to suggest that this wing neurogenesis in the newborn adult flies was influenced by genetic determinants such as the frequency dependent for gene and by environmental cues such as population density. Conclusions We demonstrate that the neuronal architecture in the adult Drosophila wing is unfinished when the flies emerge from their pupae. This unexpected developmental step might be crucial for generating non-heritable variants and phenotypic plasticity. This might therefore constitute an advantage in an unstable ecological system and explain much regarding the ability of Drosophila to robustly adapt to their environment

Inside the brain of an elite athlete: The neural processes that support high achievement in sports

Events like the World Championships in athletics and the Olympic Games raise the public profile of competitive sports. They may also leave us wondering what sets the competitors in these events apart from those of us who simply watch. Here we attempt to link neural and cognitive processes that have been found to be important for elite performance with computational and physiological theories inspired by much simpler laboratory tasks. In this way we hope to inspire neuroscientists to consider how their basic research might help to explain sporting skill at the highest levels of performance

Session 5: Development, Neuroscience and Evolutionary Psychology

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 5: Development, Neuroscience and Evolutionary Psycholog

Aerospace medicine and Biology: A continuing bibliography with indexes, supplement 177

This bibliography lists 112 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1978

Aerospace medicine and biology. A continuing bibliography with indexes, supplement 195

This bibliography lists 148 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1979

Aerospace Medicine and Biology: A continuing bibliography, supplement 191

A bibliographical list of 182 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1979 is presented