Bio-inspired Computing Machines: Towards Novel Computational Architectures

according action activation adaptive algorithm allow application approach architecture array artificial automaton basic behavior binary decision bits block called cell cellular Chapter circuit columns complete computation condition configuration connections coordinate corresponding counter defined depends described diagram direction dynamic element environment evolution evolutionary evolved example executed fault Figure final fitness four FPGA function gene genetic genome given hardware head implementation individuals initial input instruction learning logic machine means mechanism memory microprogram module molecule MUXTREE neighbor neural network neuron object operation organism output parallel performance population position possible present probability problem productions random realization reinforcement represented requires robot rule selection self-repair self-replication signal simple single solution space spare specifications step string structure synaptic tape task tree unit universal variable weights