Read the Convention Concerning the Exchange of Greek and Turkish Populations (30 January 1923) Read the Convention Relating to the Regime of the Straits (24 July 1923) Read the Convention Relating to the Regime of the Straits (24 July 1923)
HR-Net - Hellenic Resources Network Compact version
Today's Suggestion
Read The "Macedonian Question" (by Maria Nystazopoulou-Pelekidou)
HomeAbout HR-NetNewsWeb SitesDocumentsOnline HelpUsage InformationContact us
Thursday, 28 March 2024
 
News
  Latest News (All)
     From Greece
     From Cyprus
     From Europe
     From Balkans
     From Turkey
     From USA
  Announcements
  World Press
  News Archives
Web Sites
  Hosted
  Mirrored
  Interesting Nodes
Documents
  Special Topics
  Treaties, Conventions
  Constitutions
  U.S. Agencies
  Cyprus Problem
  Other
Services
  Personal NewsPaper
  Greek Fonts
  Tools
  F.A.Q.
 

Workshop on Biologically-Inspired Machine Learning, Crete, July

Conferences in and about Greece Directory - Previous Article - Next Article

From: "HR-Net News Distribution Manager" <dist@hri.org>

Originally From: John Demiris <johnde@dai.ed.ac.uk>

Biologically-inspired Machine Learning

A workshop during ACAI-99, 14-15 July 1999, Crete, Greece

http://www.cogsci.ed.ac.uk/~biml/

Call for Papers and Participation

The BIML workshop will take place during two afternoon sessions (July 14th and 15th) of ACAI-99, which will take place between 5-16 July 1999, at Chania in the island of Crete, Greece. It will consist of invited and contributed talks, and several panel and small-group discussions to encourage a genuinely interactive atmosphere.

Technical description:

The biologically-inspired machine learning approach is attractive not only as a methodology for the development and testing of theories of learning in biological systems, but also as an approach for the design of practical machine learning systems. The research methodology of this approach fuses techniques from several disciplines, including Artificial Intelligence, Cognitive Science, Psychology, Neuroscience, Simulation/Modelling, and Robotics. It is the intention of this workshop to examine the interplay between biological and artificial learning, illuminate the commonalities and differences, and lead to a fruitful exchange of ideas and techniques. Topics of interest include but are not restricted to:

  • modelling of cognitive, perceptual and motor development and adaptation in humans and animals
  • modelling of learning in infants
  • modelling of brain and cognitive disorders and recovery
  • bio-inspired robot learning
  • artificial neural networks
  • evolutionary approaches to learning
  • learning in social environments by observation, imitation and cooperation.

Program committee:

  • Frederic Alexandre, Cortex Group, INRIA-Lorraine/CRIN-CNRS, France.
  • Luc Berthouze, Humanoid Interaction Laboratory, ETL, Japan.
  • Andreas Birk, Artificial Intelligence Laboratory, VUB, Belgium.
  • Kerstin Dautenhahn, Department of Cybernetics, U. Reading, UK.
  • John Hallam, Institute of Perception, Action and Behaviour, U. Edinburgh, UK.
  • Gillian Hayes, Institute of Perception, Action and Behaviour, U. Edinburgh, UK.
  • Dolores Canamero, Artificial Intelligence Research Institute, CSIC, Barcelona, Spain.
  • Frederic Kaplan, Sony CSL, Paris, France.
  • Risto Miikkulainen, Dept. of Computer Science, University of Texas, Austin, USA
  • Chrystopher Nehaniv, Interactive Systems Engineering Group, U. Hertfordshire, UK.
  • Stefan Schaal, Computational Learning and Motor Control Lab, USC/ERATO, USA/Japan.
  • Patrick van der Smagt, Institute of Robotics and System Dynamics, German Aerospace Center, Germany.

Paper submission:

Papers describing research in Biologically-inspired Machine Learning are welcome. Submitted papers should be up to six A4 pages (two columns, single-spaced, body text size 10 pt), should be in Postscript format, and should be sent by email to biml@cogsci.ed.ac.uk. Papers should include full contact details (including email address) and affiliation of authors. In addition to regular papers, graduate students and other people interested in participating in this workshop can send a summary of their research work (max. two pages). All accepted full papers will be included in the workshop proceedings. Selected summaries will be included if space permits.

Registration:

All participants of the ACAI-99 main event will be able to participate in the workshop without extra cost. The registration fee for attending the workshop only will be 150 ECU (to include coffee breaks and the workshop's proceedings).

Please note that since the number of participants is limited, priority will be given to people submitting full papers or short research summaries.

Student Grants:

Students can apply for grants to partially cover the expenses associated with attending ACAI-99 (and the workshop). Grants from ECCAI and from the ACAI organising committee are available. See main ACAI page (under `registration') for more details.

Timetable:

March 15: deadline for submission of papers and research summaries.
March 30: notification of acceptance/rejection.
April 15: deadline for submission of final camera-ready manuscripts.
July 14-15: workshop in Greece.

Organisers:

John Demiris
Institute of Perception, Action and Behaviour
Division of Informatics
University of Edinburgh, 5 Forrest Hill, Edinburgh EH1 2QL,
Scotland, UK
E-mail: johnde@dai.ed.ac.uk

Gert Westermann
Institute for Adaptive and Neural Computation
Division of Informatics
University of Edinburgh, 2 Buccleuch Place, Edinburgh EH8 9LW,
Scotland, UK
E-mail: gert@cogsci.ed.ac.uk

WWW links with up-to-date information about BIBL and ACAI-99:

BIML workshop: http://www.cogsci.ed.ac.uk/~biml/
ACAI-99: http://www.iit.demokritos.gr/skel/eetn/acai99/index.html


Conferences in and about Greece Directory - Previous Article - Next Article
Back to Top
Copyright © 1995-2023 HR-Net (Hellenic Resources Network). An HRI Project.
All Rights Reserved.

HTML by the HR-Net Group / Hellenic Resources Institute, Inc.
misc2html v2.01 run on Saturday, 6 March 1999 - 19:37:20 UTC