Connectionists: Research (PhD) studentships available (Artificial Life/Bio-Inspired Robotics)

[Daniel Polani]

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		RESEARCH (PhD) STUDENTSHIPS AVAILABLE

   Adaptive Systems Research Group http://adapsys.feis.herts.ac.uk/
       University of Hertfordshire http://perseus.herts.ac.uk/

 Contact: Dr. Daniel Polani, Principal Lecturer d.polani at herts.ac.uk

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PhD Studentships are available at the Adaptive Systems Research Group
in the areas (among others) of Evolution of Sensors (Theory and
Robotics), Principles in Perception-Action Loops of Artificial and
Biological Systems, Bio-inspired Learning Methods for Complex Agent
Systems. All these fields can be considered subareas of Artificial
Life which is a central interest of our group.

We use robotics and mathematical models to create analytical,
predictive and constructive models of biologically relevant scenarios.
The idea is to understand how biological systems manage to ``climb''
the enormously intransparent complexity and intelligence obstacle to
achieve the impressive variety of capabilities that is found in living
systems. For this purpose, we develop mathematical, simulation and
robotic models of these systems. The goal is, on the one hand, to
understand biology, but, on the other hand, also to use this
understanding to discover novel ``out-of-the-box'' principles for
building artificial systems.
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EVOLUTION OF SENSORS (ROBOTICS AND THEORY)

In recent years, the study of the evolution of sensors in living
beings and in artificial systems has led to surprising insights into
some of the driving forces of evolution. There is increasing evidence
that the ``discovery'' of novel sensors by evolution contributes very
significantly to selective pressure acting on living beings and may be
one of the main sources of complexification and diversification during
evolution. On the other hand, there are indications that sensor
evolution itself is driven by the selection pressures resulting from
given embodiments and informatory-ecological niches. The research of
the last years allowed to identify the sources for this pressure in a
quantitative way.

A project in this direction will further develop theory and/or
robotical models of sensor evolution of how environmental information
can be tapped; thus it will contribute to unraveling one of the
central mysteries of how the significant selection pressures produced
by evolution can emerge and possibly be used for artificial systems.
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PRINCIPLES IN PERCEPTION-ACTION LOOPS OF ARTIFICIAL AND BIOLOGICAL
SYSTEMS

Living or artificial agents all share the property of acquiring
environmental information (perception), processing this information
and then acting upon it. Based on this minimal agent model, our
group's recent research has found quantitative ways to derive a
significant number of mechanisms from information-theoretic principles
whereby agents can achieve increasingly more sophisticated models of
their environment.

Unlike learning models from classical Artificial Intelligence,the
resulting agent controls are not easily human-readable; they also
differ from artificial neural networks, where significant aspects of
the architecture are pre-designed by humans. In fact, it turns out
that the encodings discovered by the agents have qualitative
similarities to encoding applied in biological neurons.

Similar simple principles can be used in robots to recover a wider
variety of phenomena observed in biological agents from common
grounds. This is a powerful indication that biology and evolution may
reuse the same (or similar) principles to create the wide variety of
capabilites that we find in nature -- and it provides a methodology to
recreate these capabilites in artificial systems.

A project in this direction will apply quantitative principled methods
to discover algorithms which will provide robots and robotic models to
exhibit similar sensomotoric phenomena as living beings.
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BIO-INSPIRED LEARNING METHODS FOR COMPLEX AGENT SYSTEMS

A further research area is the use of biologically inspired learning
principles to allow complex agent systems to learn. Complex agent
systems can be individual complex agents or larger agent groups
(swarms) that, thanks to the size of their group, display complex
emergent and/or self-organizing behaviour or require intricate
coordination because of their task. Examples for this are ant colonies
or RoboCup scenarios (robotic soccer).

Understanding and managing the learning problem for such agent teams
or complex agents is a very active research field and our
information-theoretic methods (as mentioned in the previous sections)
provide a novel, powerful and principled approach to it.

A PhD project in this direction will develop principled and
generalizable approaches to construct learning and adaptation models
whereby complex agent systems can incrementally learn to master their
environment and identify and solve tasks.
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FURTHER INFORMATION ON THE RESEARCH AREA

For information on the research, please also consult the web page of
Dr. Daniel Polani (http://homepages.feis.herts.ac.uk/~comqdp1/) and
the respective publications
(http://homepages.feis.herts.ac.uk/~comqdp1/publications.html). If you
are interested in above areas, please make sure you mention the
keywords (``Evolution of Sensors'', ``Perception-Action Loop'' etc.)
in your application. If you have questions, please contact
d.polani at herts.ac.uk.
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APPLICANTS

Interested candidates will have very strong programming background,
and very strong mathematical/analytical skills (e.g. due to a
Computer Science/Mathematics/Physics degree) and a keen interest in
interdisciplinary research, combining biological evidence with
theoretical models and/or implementing them on simulated or real
robotic systems.

Applicants are urged to apply as soon as possible.
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ABOUT THE GROUP

The PhD studentships offer the opportunity to work within the Adaptive
Systems Research Group, a proactive and dynamic research team with an
excellent international research profile at the University of
Hertfordshire, located not far from London, between Cambridge and
London. The group was founded and is co-organized by Prof. Kerstin
Dautenhahn and Prof. Chrystopher Nehaniv. Other core faculty members
of the group include Dr. Daniel Polani, Dr. Rene te Boekhorst, and Dr.
Lola Canamero. Current projects within the Adaptive Systems Research
Group are funded by FP6-IST, EPSRC, the Wellcome Trust and the British
Academy. The group is currently involved in the following FP6 European
projects: Euron-II, Humaine (both European Networks of Excellence),
Cogniron and RobotCub (Integrated Projects). We hosted the AISB'05
convention Social Intelligence and Interaction in Biological and
Artificial Systems that attracted an international audience of 300
participants. Research in the group is highly interdisciplinary and
strongly biologically inspired, but also has a strong theoretical
foundation.

Adaptive Systems are computational, software, robotic, or biological
systems that are able to deal with and 'survive' in a dynamically
changing environment. We pursue a bottom-up approach to Artificial
Intelligence that emphasizes the embodied and situated nature of
biological or artificial systems that have evolved and are adapted to
a particular environmental context. The Adaptive Systems Research
Group has excellent research facilities for research staff, including
numerous robotic platforms, covering the spectrum from miniature
Khepera robots, dog-like AIBO robots, to human-sized robots
(PeopleBots), as well as humanoid robots developed in our group. We
are dedicated to excellence in research, and, while providing a
collaborative and supportive working environment, expect PhD students
to show great enthusiasm and determination for their work. Candidates
need to provide evidence of excellent research potential that can lead
to significant contributions to knowledge as part of a PhD thesis.

Successful candidates may be eligible for a research studentship award
from the University in some of these areas (equivalent to about £9000
per annum bursary plus the payment of the standard UK student fees).
Self-funded students might also consider to pursue other research
topics that senior academic members of the Adaptive Systems research
group are active in, please consult http://adapsys.feis.herts.ac.uk/
for more information.

Other areas in our research group are advertised at:
http://homepages.feis.herts.ac.uk/~comqkd/AS-Studentshipadvert.html

For an application form, please contact:

Mrs Lorraine Nicholls,
Research Student Administrator,
STRI, Faculty of Engineering and Information Sciences,
University of Hertfordshire,
College Lane,
Hatfield, Herts, AL10 9AB
United Kingdom

Tel: +44 (0) 1707 286083 Fax: +44 (0) 1707 284185 or email:
L.Nicholls at herts.ac.uk.

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Pdf and HTML versions of this document can be found on

http://homepages.feis.herts.ac.uk/~comqdp1/Studentships/SE_2005.pdf
http://homepages.feis.herts.ac.uk/~comqdp1/Studentships/SE_2005/SE_2005.html

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