Titlebook: Evolvable Systems: From Biology to Hardware; 9th International Co Gianluca Tempesti,Andy M. Tyrrell,Julian F. Miller Conference proceedings

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Systemic Computation Using Graphics Processorsding parallelism. The approach has been proven through two existing implementations and many biological models and visualizations. However to date the systemic computer implementations have all been sequential simulations that do not exploit the true potential of the model. In this paper the first p

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Performance Evaluation and Scaling of a Multiprocessor Architecture Emulating Complex SNN AlgorithmsNs) is reported. After describing the architecture and the complex SNN algorithm mapping, the performance study demonstrates that the system can emulate up to 10,000 300-synapse neurons in real time at 64 MHz with conventional FPGAs. Important improvements can be achieved by using advanced technolog

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Evolution of Analog Circuit Models of Ion Channels ion channels embedded in a neuron’s cell membrane as a capacitor in parallel with batteries and resistors. However, to match the predictions of the model with their empirical electrophysiological data, Hodgkin and Huxley described the nonlinear resistors using a complex system of coupled differenti

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HyperNEAT for Locomotion Control in Modular Robotsocation in an organism they will end up. If the organism is to be controlled autonomously by the constituent robots, an evolutionary algorithm that evolves the controllers can only develop a single genome that will have to suffice for every individual robot. However, the robots should show different

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Bio-inspired Self-testing Configurable Circuitsle processes. The goal of our paper is to demonstrate how these bio-inspired mechanisms and their underlying processes perform on cellular architectures. The hardware description of the molecule with all its bio-inspired mechanisms leads to the simulation of an image processing array and an arithmet

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Evolutionary Design of Reconfiguration Strategies to Reduce the Test Application Time before test is applied. Selection of the gates for reconfiguration was performed using a very time consuming deterministic recursive search algorithm. In this paper, a new method is proposed for selection of the gates in order to reduce the test application time. The method utilizes an evolutionary

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https://doi.org/10.1007/978-3-662-40226-9standard CGP. We argue that considering fully functional but not necessarily smallest-discovered individual as the parent for new population can decrease the number of harmful mutations and so improve the search space exploration. This phenomenon was confirmed on common benchmarks such as combinational multipliers and the LGSynth91 circuits.