On Thu, Nov 20, 2008 at 3:06 PM, Mark Waser <[EMAIL PROTECTED]> wrote: > Yeah. Great headline -- "Man beats dead horse beyond death!" > > I'm sure that there will be more details at 11. > > Though I am curious . . . . BillK, why did you think that this was worth > posting? >
??? Did you read the article? ----------------------- Quote: 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. Roy's theory undermines the roots of connectionism, and that's why his ideas have experienced a tremendous amount of resistance from the cognitive science community. For the past 15 years, Roy has engaged researchers in public debates, in which it's usually him arguing against a dozen or so connectionist researchers. Roy says he wasn't surprised at the resistance, though. "I was attempting to take down their whole body of science," he explained. "So I would probably have behaved the same way if I were in their shoes." No matter exactly where or what the brain controllers are, Roy hopes that his theory will enable research on new kinds of learning algorithms. Currently, restrictions such as local and memoryless learning have limited AI designers, but these concepts are derived directly from that idea that control is local, not high-level. Possibly, a controller-based theory could lead to the development of truly autonomous learning systems, and a next generation of intelligent robots. The sentiment that the "science is stuck" is becoming common to AI researchers. In July 2007, the National Science Foundation (NSF) hosted a workshop on the "Future Challenges for the Science and Engineering of Learning." The NSF's summary of the "Open Questions in Both Biological and Machine Learning" [see below] from the workshop emphasizes the limitations in current approaches to machine learning, especially when compared with biological learners' ability to learn autonomously under their own self-supervision: "Virtually all current approaches to machine learning typically require a human supervisor to design the learning architecture, select the training examples, design the form of the representation of the training examples, choose the learning algorithm, set the learning parameters, decide when to stop learning, and choose the way in which the performance of the learning algorithm is evaluated. This strong dependence on human supervision is greatly retarding the development and ubiquitous deployment of autonomous artificial learning systems. Although we are beginning to understand some of the learning systems used by brains, many aspects of autonomous learning have not yet been identified." Roy sees the NSF's call for a new science as an open door for a new theory, and he plans to work hard to ensure that his colleagues realize the potential of the controller model. Next April, he will present a four-hour workshop on autonomous machine learning, having been invited by the Program Committee of the International Joint Conference on Neural Networks (IJCNN). ----------------- Now his 'new' theory may be old hat to you personally, but apparently not to the majority of AI researchers, (according to the article). He must be saying something a bit unusual to have been fighting for ten years to get it published and accepted enough for him to now have been invited to do a workshop on his theory. BillK ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com