Abstract
The classical approach to using utility functions suffers from the drawback of having to design and tweak the functions on a case by case basis. Inspired by examples from the animal kingdom, social sciences and games we propose empowerment, a rather universal function, defined as the information-theoretic capacity of an agent’s actuation channel. The concept applies to any sensorimotoric apparatus. Empowerment as a measure reflects the properties of the apparatus as long as they are observable due to the coupling of sensors and actuators via the environment.
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Editors and Affiliations
Natural Computation Group, University of Kent, CT2 7NF, Canterbury, UK
Mathieu S. Capcarrère
Computing Laboratory and Centre for BioMedical Informatics, University of Kent, CT2 7NF, Canterbury, UK
Alex A. Freitas
Computer Science Department, University College London, London, UK
Peter J. Bentley
Computing Laboratory, University of Kent, Canterbury, UK
Colin G. Johnson
Department of Electronics, University of York, YO10 5DD, Heslington, York, UK
Jon Timmis
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Klyubin, A.S., Polani, D., Nehaniv, C.L. (2005). All Else Being Equal Be Empowered. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_75
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DOI: https://doi.org/10.1007/11553090_75
Publisher Name: Springer, Berlin, Heidelberg
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Keywords
- Utility Function
- Mutual Information
- Channel Capacity
- Conditional Probability Distribution
- Average Short Path
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
