Cellular automata machines: a new environment for modeling
Cellular automata machines: a new environment for modeling
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Analysis of unconventional evolved electronics
Communications of the ACM
Spikes: exploring the neural code
Spikes: exploring the neural code
Building an artificial brain using an FPGA based CAM-Brain machine
Applied Mathematics and Computation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A ``Spike Interval Information Coding'' Representation for ATR's CAM-Brain Machine (CBM)
ICES '98 Proceedings of the Second International Conference on Evolvable Systems: From Biology to Hardware
CoDi-1Bit: A Simplified Cellular Automata Based Neuron Model
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
A system for evolving neural architectures
Proceedings of the 50th Annual Southeast Regional Conference
FPGA-based biophysically-meaningful modeling of olivocerebellar neurons
Proceedings of the 2014 ACM/SIGDA international symposium on Field-programmable gate arrays
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This article introduces the “CAM-Brain Machine” (CBM), an FPGA based piece of hardware which implements a genetic algorithm (GA) to evolve a cellular automata (CA) based neural network circuit module, of approximately 1,000 neurons, in about a second, i.e., a complete run of a GA, with 10,000s of circuit growths and performance evaluations. Up to 65,000 of these modules, each of which is evolved with a humanly specified function, can be downloaded into a large RAM space, and interconnected according to humanly specified artificial brain architectures. This RAM, containing an artificial brain with up to 75 million neurons, is then updated by the CBM at a rate of 130 billion CA cells per second. Such speeds should enable real time control of robots and hopefully the birth of a new research field that we call “brain building.” The first such artificial brain, to be built in 2000 and beyond, will be used to control the behaviors of a life sized robotkitten called “Robokitty.”