Information in Perception and Action
Naftali Tishby · Daniel Polani · Tobias Jung

Fri Dec 7th 07:30 AM -- 06:30 PM @ Emerald Bay 3, Harveys Convention Center Floor (CC)
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Since its inception for describing the laws of communication in the 1940's, information theory has been considered in fields beyond its original application area and, in particular, it was long attempted to utilize it for the description of intelligent agents. Already Attneave (1954) and Barlow (1961) suspected that neural information processing might follow principles of information theory and Laughlin (1998) demonstrated that information processing comes at a high metabolic cost; this implies that there would be evolutionary pressure pushing organismic information processing towards the optimal levels of data throughput predicted by information theory. This becomes particularly interesting when one considers the whole perception-action cycle, including feedback. In the last decade, significant progress has been made in this direction, linking information theory and control. The ensuing insights allow to address a large range of fundamental questions pertaining not only to the perception-action cycle, but to general issues of intelligence, and allow to solve classical problems of AI and machine learning in a novel way.

The workshop will present recent work on progress in AI, machine learning, control, as well as biologically plausible cognitive modeling, that is based on information theory.

Author Information

Naftali Tishby (The Hebrew University Jerusalem)

Naftali Tishby, is a professor of computer science and the director of the Interdisciplinary Center for Neural Computation (ICNC) at the Hebrew university of Jerusalem. He received his Ph.D. in theoretical physics from the Hebrew University and was a research staff member at MIT and Bell Labs from 1985 to 1991. He was also a visiting professor at Princeton NECI, the University of Pennsylvania and the University of California at Santa Barbara. Dr. Tishby is a leader of machine learning research and computational neuroscience. He was among the first to introduce methods from statistical physics into learning theory, and dynamical systems techniques in speech processing. His current research is at the interface between computer science, statistical physics and computational neuroscience and concerns the foundations of biological information processing and the connections between dynamics and information.

Daniel Polani (University of Hertfordshire)
Tobias Jung (University of Liege)

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