- author = "Hugo {de Garis} and Andrzej Buller and Michael Korkin and Felix Gers and Norberto Eija Nawa and Michael Hough",
- title = "{ATR}'s Artificial Brain {(``CAM-Brain'')} Project: A Sample of What Individual {``CoDi-1Bit''} Model Evolved Neural Net Modules Can Do with Digital and Analog {I/O}",
- booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference",
- year = "1999",
- editor = "Wolfgang Banzhaf and Jason Daida and Agoston E. Eiben and Max H. Garzon and Vasant Honavar and Mark Jakiela and Robert E. Smith",
- volume = "2",
- pages = "1233",
- address = "Orlando, Florida, USA",
- publisher_address = "San Francisco, CA 94104, USA",
- month = "13-17 " # jul,
- publisher = "Morgan Kaufmann",
- keywords = "genetic algorithms, genetic programming, ANN, poster papers",
- ISBN = "1-55860-611-4",
-
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco1999/garis_1999_aabpaswimennmcddai.pdf",
- size = "1 page",
-
notes = "This work presents a sample of what evolved neural net
circuit modules using the socalled CoDi-1Bit neural net
model [5] 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 behaviours
of a kitten robot Robokoneko [2][3][4]. 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) [6]. It implements the
CoDi-1Bit model, and was delivered to ATR in May 1999.
The CBM should make practical the assemblage of 10,000s
of evolved neural net modules into humanly defined
artificial brain architectures. 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. This work
reports on some of the results of these simulations,
for which the input/output is either binary or
analog.
May 2020 Notes from https://dl.acm.org/doi/10.5555/787262.787793 as close to abstract.
GECCO-99 A joint meeting of the eighth international conference on genetic algorithms (ICGA-99) and the fourth annual genetic programming conference (GP-99)
11 Nov 2005 Ten page version at citeseer.ist.psu.edu/22456.html See also CEC 1999",
