In the late '90s, Asim Roy, a professor of information systems at
Arizona State University, began to write a paper on a new brain theory.
Now, 10 years later and after several rejections and resubmissions, the
paper “Connectionism, Controllers, and a Brain Theory” has finally been
published in the November issue of IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans.
However, Roy’s controversial ideas on how the brain works and learns probably won’t immediately win over many of his colleagues, who have spent decades teaching robots and artificial intelligence (AI) systems how to think using the classic connectionist theory of the brain. Connectionists propose that the brain consists of an interacting network of neurons and cells, and that it solves problems based on how these components are connected. In this theory, there are no separate controllers for higher level brain functions, but all control is local and distributed fairly equally among all the parts.
In his paper, Roy argues for a controller theory of the brain. In this view, there are some parts of the brain that control other parts, making it a hierarchical system. In the controller theory, which fits with the so-called computational theory, the brain learns lots of rules and uses them in a top-down processing method to operate. In 1997, IBM’s Deep Blue computer, which famously defeated world chess champion Garry Kasparov, operated based on countless rules entered by its programmers.
More information: Roy, Asim. “Connectionism, Controllers, and a Brain Theory.” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol. 38, No. 6, November 2008.
Rumelhart, D. E. and J. L. McClelland, Eds., Parallel Distributed Processing: Explorations in Microstructure of Cognition, vol. 1. Cambridge, MA: MIT Press, 1986, pp. 318–362.
NSF’s summary of the “Open Questions in Both Biological and Machine Learning” http://www.cnl.salk.edu/Media/NSFWorkshopReport.v4.pdf
ANNIE Conference Web site http://annie.mst.edu/annie_2008/ANNIE2008.html
http://www.physorg.com/news146319784.html
However, Roy’s controversial ideas on how the brain works and learns probably won’t immediately win over many of his colleagues, who have spent decades teaching robots and artificial intelligence (AI) systems how to think using the classic connectionist theory of the brain. Connectionists propose that the brain consists of an interacting network of neurons and cells, and that it solves problems based on how these components are connected. In this theory, there are no separate controllers for higher level brain functions, but all control is local and distributed fairly equally among all the parts.
In his paper, Roy argues for a controller theory of the brain. In this view, there are some parts of the brain that control other parts, making it a hierarchical system. In the controller theory, which fits with the so-called computational theory, the brain learns lots of rules and uses them in a top-down processing method to operate. In 1997, IBM’s Deep Blue computer, which famously defeated world chess champion Garry Kasparov, operated based on countless rules entered by its programmers.
More information: Roy, Asim. “Connectionism, Controllers, and a Brain Theory.” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol. 38, No. 6, November 2008.
Rumelhart, D. E. and J. L. McClelland, Eds., Parallel Distributed Processing: Explorations in Microstructure of Cognition, vol. 1. Cambridge, MA: MIT Press, 1986, pp. 318–362.
NSF’s summary of the “Open Questions in Both Biological and Machine Learning” http://www.cnl.salk.edu/Media/NSFWorkshopReport.v4.pdf
ANNIE Conference Web site http://annie.mst.edu/annie_2008/ANNIE2008.html
http://www.physorg.com/news146319784.html
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