Special Issue "Information Theoretic Incentives for Cognitive Systems"

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A special issue of Entropy (ISSN 1099-4300).

Deadline for manuscript submissions: 28 February 2015

Special Issue Editors

Guest Editor
Dr. Christoph Salge
Adaptive Systems Research Group,University of Hertfordshire, College Lane, AL10 9AB Hatfield, UK
Website: http://homepages.stca.herts.ac.uk/~cs08abi
E-Mail: c.salge@herts.ac.uk
Phone: +44 1707 28 4490
Interests: Intrinsic Motivation (Empowerment); Self-Organization; Guided Self-Organization; Information-Theoretic Incentives for Social Interaction; Information-Theoretic Incentives for Swarms; Information Theory and Computer Game AI

Guest Editor
Dr. Georg Martius
Cognition and Neurosciences, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Website: http://www.mis.mpg.de/jjost/members/georg-martius.html
E-Mail: martius@mis.mpg.de
Phone: +49 341 9959 545
Interests: Autonomous Robots; Self-Organization; Guided Self-Organization; Information Theory; Dynamical Systems; Machine Learning; Neuroscience of Learning; Optimal Control

Guest Editor
Dr. Keyan Ghazi-Zahedi
Information Theory of Cognitive Systems, Max Planck Institute for Mathematics in the Sciences Inselstrasse 22, 04103 Leipzig, Germany
Website: http://personal-homepages.mis.mpg.de/zahedi
E-Mail: zahedi@mis.mpg.de
Phone: +49 341 9959 535
Interests: Embodied Artificial Intelligence; Information Theory of the Sensorimotor Loop; Dynamical Systems; Cybernetics; Self-organisation; Synaptic plasticity; Evolutionary Robotics

Guest Editor
Dr. Daniel Polani
Department of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK
Website: http://homepages.feis.herts.ac.uk/~comqdp1/
E-Mail: d.polani@herts.ac.uk
Interests: artificial intelligence; artificial life; information theory for intelligent information processing; sensor Evolution; collective and multiagent systems

Special Issue Information

Dear Colleagues,

In recent years, ideas such as "life is information processing" or "information holds the key to understanding life" have become more common. However, how can information, or more formally Information Theory, increase our understanding of life, or life-like systems?

Information Theory not only has a profound mathematical basis, but also typically provides an intuitive understanding of processes, such as learning, behavior and evolution terms of information processing.

In this special issue, we are interested in both: a.) the information-theoretic formalization and quantification of different aspects of life, such as driving forces of learning and behavior generation, information flows between neurons, swarm members and social agents, and information theoretic aspects of evolution and adaptation and b.) the simulation and creation of life-like systems with previously identified principles and incentives.

Topics with relation to artificial and natural systems:

  • information theoretic intrinsic motivations
  • information theoretic quantification of behavior
  • information theoretic guidance of artificial evolution
  • information theoretic guidance of self-organization
  • information theoretic driving forces behind learning
  • information theoretic driving forces behind behavior
  • information theory in swarms
  • information theory in social behavior
  • information theory in evolution
  • information theory in the brain
  • information theory in system-environment distinction
  • information theory in the perception action loop
  • information theoretic definitions of life

Dr. Christoph Salge
Dr. Georg Martius
Dr.  Keyan Ghazi-Zahedi
Dr. Daniel Polani
Guest Editors

[1] A. S. Klyubin, D. Polani, and C.L. Nehaniv. Empowerment: A Universal Agent-Centric Measure of Control. In Proc. CEC 2005.
[2] G. Martius, R. Der, and N. Ay. Information driven self-organization of complex robotic behaviors. PLoS ONE, 8(5):e63400, 2013.
[3] D. Y. Little, F. T. Sommer: Learning and exploration in action-perception loops. Frontiers in Neural Circuits, 2013
[4] Max Lungarella, Olaf Sporns, Information self-structuring: key principle for learning and development. Proc. ICDL, 2005.
[5] Polani, Daniel. "Information: currency of life?." HFSP journal 3.5 (2009): 307-316.
[6] K. Zahedi, N. Ay, and R. Der. Higher coordination with less control – a result of information maximization in the sensori-motor loop. Adaptive Behavior, 18(3–4):338–355, 2010.
[7] K. Zahedi and N. Ay. Quantifying morphological computation. Entropy, 15(5):1887–1915, 2013.
[8] R. Pfeifer, M. Lungarella, and F. Iida. Self-organization, embodiment, and biologically inspired robotics. Science, 318(5853):1088–1093, 2007.
[9] Salge, Christoph, Cornelius Glackin, and Daniel Polani. "Changing the Environment Based on Empowerment as Intrinsic Motivation." Entropy 16.5 (2014): 2789-2819.

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed Open Access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs).

Published Papers

No papers have been published in this special issue yet.

Last update: 20 August 2014

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