TY - GEN
T1 - On NSF "open questions," some external properties of the brain as a learning system and an architecture for autonomous learning
AU - Roy, Asim
PY - 2010
Y1 - 2010
N2 - The 2007 NSF workshop report titled "Future Challenges for the Science and Engineering of Learning" (http://www.cnl.salk.edu/Media/ NSFWorkshopReport.v4.pdf) raises lots of questions about how the brain works and learns and they have important implications for the development of autonomous adaptive systems. The report also defines some general characteristics of biological learners that, in essence, impose constraints on any kind of learning systems that we call brain-like. This paper examines these general characteristics of biological learners, as defined in the NSF report, and relates them to a set of properties of brain-like learning defined as early as 1994 [12]. The paper also shows how a control theoretic architecture for autonomous learning systems mitigates or resolves many of the "open questions" posed by the NSF report. It also provides some recent evidence from neuroscience on the nature of learning in biological systems that support the notion that the brain has a control theoretic architecture.
AB - The 2007 NSF workshop report titled "Future Challenges for the Science and Engineering of Learning" (http://www.cnl.salk.edu/Media/ NSFWorkshopReport.v4.pdf) raises lots of questions about how the brain works and learns and they have important implications for the development of autonomous adaptive systems. The report also defines some general characteristics of biological learners that, in essence, impose constraints on any kind of learning systems that we call brain-like. This paper examines these general characteristics of biological learners, as defined in the NSF report, and relates them to a set of properties of brain-like learning defined as early as 1994 [12]. The paper also shows how a control theoretic architecture for autonomous learning systems mitigates or resolves many of the "open questions" posed by the NSF report. It also provides some recent evidence from neuroscience on the nature of learning in biological systems that support the notion that the brain has a control theoretic architecture.
UR - http://www.scopus.com/inward/record.url?scp=79959438166&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79959438166&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2010.5596769
DO - 10.1109/IJCNN.2010.5596769
M3 - Conference contribution
AN - SCOPUS:79959438166
SN - 9781424469178
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Y2 - 18 July 2010 through 23 July 2010
ER -