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ATR's artificial brain (CAM-brain) project: a sample of what individual CoDi-1Bit model evolved neural net modules can do

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4 Author(s)
H. de Garis ; ATR-HIP, Kyoto, Japan ; M. Korkin ; F. Gers ; M. Hough

The paper presents a sample of what evolved neural net circuit modules using the so called “CoDi-1Bit” neural net model can do. This work is part of an 8 year research project at ATR which aims to build an artificial brain containing a billion neurons by the year 2001, that will be used to control the behaviors of a kitten robot “Robokoneko”. It looks as though the figure is more likely to be 40 million, but the numbers are not of great concern. What is more important is the issue of evolvability of the cellular automata (CA) based neural net circuits which grow and evolve in special FPGA (field programmable gate array) hardware, at hardware speeds, e.g. updating 150 billion CA cells per second, and performing a complete run of a genetic algorithm, i.e. tens of thousands of circuit growths and fitness evaluations, to evolve the elite neural net circuit in about 1 second. The specialized hardware which performs this evolution is labeled the CAM-Brain Machine (CBM). It implements the CoDi-1Bit model, and will be delivered to ATR probably in January 1999. The CBM should make practical the assemblage of 10000s of evolved neural net modules into humanly defined artificial brains. For the past few months, the latest hardware version of the CBM has been simulated in software to see just how evolvable and functional individual evolved modules can be. The paper reports on some of the results of these simulations

Published in:

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on  (Volume:3 )

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