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Constructing Phenomenal Knowledge in an Unknown Noumenal Reality

Authors :
Olivier L. Georgeon
Florian J. Bernard
Amélie Cordier
Traces, Web, Education, Adaptation, Knowledge (TWEAK)
Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS)
Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL)
Université de Lyon-École Centrale de Lyon (ECL)
Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon)
Université de Lyon-Université Lumière - Lyon 2 (UL2)
Source :
BICA, International Conference on Biologially Inspired Cognitive Architecture, International Conference on Biologially Inspired Cognitive Architecture, Nov 2015, Lyon, France. ⟨10.1016/j.procs.2015.12.177⟩
Publication Year :
2015
Publisher :
Elsevier BV, 2015.

Abstract

International audience; In 1781, Immanuel Kant argued that cognitive agents ignored the underlying structure of their world " as such " (the noumenal reality), and could only know phenomenal reality (the world " as it appears " through their experience). We introduce design principles to implement these theoretical ideas. Our agent's input data is not a direct function of the environment's state as it is in most symbolic or reinforcement-learning models. The agent is designed to discover and learn regularities in its stream of experience and to construct knowledge about phenomena whose hypothetical presence in the environment explains these regularities. We report a proof-of-concept experiment in which the agent constructs categories of phenomena, and exploits this knowledge to satisfy innate preferences. This work suggests a new approach to cognitive modeling that focuses on the agent's internal stream of experience. We argue that this approach complies with theories of embodied cognition and enaction.

Details

ISSN :
18770509
Volume :
71
Database :
OpenAIRE
Journal :
Procedia Computer Science
Accession number :
edsair.doi.dedup.....d62ce23f32def6556eb56547fd2d09ac
Full Text :
https://doi.org/10.1016/j.procs.2015.12.177