Science at the Edge
Friday February 14, 2014
11:30am, 1400 Biomedical Physical Science Building
Towards Physics of the Mind
Leonid I. Perlovsky
Harvard University
Air Force Research Lab
lperl@rcn.com
ABSTRACT
Is physics of the mind possible? How would it differ from biophysics or neural networks?
Physics looks for the first principles describing a wide area of reality. Physics develops
testable predictive theories. The talk describes steps towards a physical theory of the mind.
Known first principles include mechanisms of concepts, emotions, the knowledge instinct,
the mind hierarchy, and dynamic logic (DL). This dynamic process-logic replaces classical
logic of static statements. DL is a basis for a mathematical theory of learning, combining the
first principles into a hierarchical mental system. DL processes "from vague to crisp," evolve
vague representation-concepts to crisp ones. Brain imaging experiments confirmed this as an
adequate model of perception and cognition.
DL overcame computational complexity plaguing modeling of the mind, artificial
intelligence, and machine learning since the 1960s. I relate this difficulty to Gödelian
problems in logic: it is a manifestation of Gödelian incompleteness in finite systems, such as
computers or brains. The mind is "not logical." Orders of magnitude improvements are
achieved in pattern recognition, data mining, information integration, financial predictions.
How does language interact with cognition? What are the mechanisms of higher cognitive
abilities? What is the beautiful? Why does music, "just sounds," affect us emotionally? Why
did these abilities emerge in evolution? Darwin called music "the greatest mystery." The DL
model gives answers and testable predictions. Some explanations are experimentally
confirmed, others remain to be tested in future.
To meet with the speaker on please contact R. Ghosh (ghosh@pa.msu.edu)