Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
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Shrinking the Genotype: L-systems for EHW?
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
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EH '02 Proceedings of the 2002 NASA/DoD Conference on Evolvable Hardware (EH'02)
ICAL 2003 Proceedings of the eighth international conference on Artificial life
POEtic tissue: an integrated architecture for bio-inspired hardware
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
An FPGA Based Test Bed for Bio Inspired Computation
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 3 - Volume 04
Evolutionary morphogenesis for multi-cellular systems
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Developmental neural heterogeneity through coarse-coding regulation
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
A coarse-coding framework for a gene-regulatory-based artificial neural tissue
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Designing a morphogenetic system for evolvable hardware
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
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This paper describes a new evolutionary mechanism developed specifically for cellular circuits. Called morphogenetic system, it is inspired by the mechanisms of gene expression and cell differentiation found in living organisms. It will be used as the phylogenetic (evolutionary) mechanism in the POEtic project. The POEtic project will deliver an electronic circuit, called the POEtic circuit, with the capability to evolve (Phylogenesis), self-repair and grow (Ontogenesis) and learn (Epigenesis). The morphogenetic system is applied to the generation of patterns and to the evolution of spiking neural networks, with experiments of pattern recognition and obstacle avoidance with robots. Experimental results show that the morphogenetic system outperforms a direct genetic coding in several experiments.