Connectionists: PhD Opportunity: Information and the Origin of Cognition

[Daniel Polani]

Do you wonder about the nature of cognition? How organisms naturally
achieve such high levels of intelligence, when it requires the
smartest engineers to come up with elaborate, clever, energy- and
data-intensive solutions to achieve pertinent effects? What are we
missing in AI? And what can we do about that?

If so, and you have a a very strong programming and computational
background, then the following PhD studentship might be of interest to
you:

      Information and the Origin of Cognition:
Natural and Artificial Intelligence and Robotics from First Principles

Shannon information is a fundamental resource in cognition and in
decision-making, from of molecular dynamics to animal brains, up to
Artificial Intelligence systems. All these complex systems need to
organize information.

We investigate the fundamental principles along which these
intelligent organizational processes take place. We ask how
increasingly powerful systems and capabilities can emerge and
self-organize spontaneously through informational principles; and
finally, how, in turn, these principles can be used to create and
understand more capable and transparent AI and robotic systems.

We offer PhD studentships researching these topics. As a candidate,
you will be interested in the whole spectrum: uncovering the
principles behind the emergence and organization of cognition from
physical and biological principles up to its application to Artificial
Intelligence and Robotics, typically based on information
theory. Possible research questions include, but are by far not
limited to:

 -  modeling cognitive structure
 -  extracting structural generalizations
 -  enabling robust decision making, minimal and flexible robotic control
 -  agents that "want": intrinsic motivations, especially, but not limited
to empowerment
 -  unlocking the role of embodiment and informational ecology
 -  using above for concrete robotics applications
 -  models of biological or Artificial Life, including questions of origin
of life and cognition from first principles.
 -  links to physics and complex systems in general


You will have a very strong first degree; a keen interest and
motivation to delve into and con- tribute to a fresh, stimulating and
fast-moving research area at the shared boundary of AI, robotics,
biology, physics, psychology, collective and social systems. An
outstanding back- ground in one of the following or related fields is
essential: Computer Science, AI, Computational/Cognitive Robotics,
Physics, Mathematics or any other relevant discipline with a
considerable quantitative/computational component. In particular, you
will demonstrate excellent programming skills in at least one major
computer language. A mathematical/numerical background would be highly
desirable. Knowledge in at least one of the following fields would be
a strong plus: probability theory, Bayesian modeling, information
theory, differential geometry, control, dynamical systems, statistical
learning data modelling/neural network techniques.

The research will take place in the vibrant, enthusiastic and creative
environment of the Adaptive Systems Research Group of the School of
Physics, Engineering and Computer Science at the University of
Hertfordshire; for interested candidates, there will also be the
special op- portunity to collaborate with the School's successful
humanoid robot RoboCup team, the Bold Hearts, with additional actively
funded projects and with research groups across the world.

More information about the topic is available from:
d.polani at herts.ac.uk

For further details and how to apply please see here:

https://www.herts.ac.uk/courses/research/phd-computer-science

and here:

https://www.jobs.ac.uk/job/DPC268/phd-studentships-in-computer-science
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