Titlebook: Evolvable Systems: From Biology to Hardware; 6th International Co J. Manuel Moreno,Jordi Madrenas,Jordi Cosp Conference proceedings 2005 Sp

充气球

The Role of Non-linearity for Evolved Multifunctional Robot Behavioris discussion is based on experiments where combinations of two behavioral tasks are incrementally evolved. The evolutionary experiments develop recurrent neural networks of general type in a systematically way. The resulting networks are investigated according to the underlying structure-function r

atrophy

An On-the-fly Evolutionary Algorithm for Robot Motion Planningotion planning consists of generating a collision-free path for a movable object among known and static obstacles. In this paper, we introduce a two stage evolutionary algorithm. The first stage is designed to compute a collision-free path in a known environment. The second stage is designed to make

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Improving the Evolvability of Digital Multipliers Using Embedded Cartesian Genetic Programming and Pestigate the use of ECGP together with a technique called Product Reduction (PR) to reduce the time required to evolve a digital multiplier. The results are compared with Cartesian Genetic Programming (CGP) with and without PR and show that ECGP improves evolvability and also that PR improves the pe

headway

Benefits of Employing an Implicit Context Representation on Hardware Geometry of CGPlvable hardware by the authors. However, conventional CGP exhibits the undesirable characteristic of positional dependence in which the specific location of genes within the chromosome has a direct or indirect influence on the phenotype. An implicit context representation of CGP (IRCGP) has been imp

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Tortuous

Hardware Implementation of 3D Self-replicationcation to the hardware implementation of 3D self-replicating structures. This self-replication process is achieved by translation and transcription of a configuration information in a three-dimensional data and signals cellular automaton (DSCA). The corresponding hardware implementation takes place

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爱哭

Implementation of Biologically Plausible Spiking Neural Networks Models on the POEtic Tissueans that learning models based on discrete dynamics have more chances to provide a ground basis for modelling the underlying mechanisms associated with plasticity processes in the brain. In this paper we shall present the physical implementation of a learning model for Spiking Neural Networks (SNN)

浸软

吸气