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A survival task for the design and the assessment of an autonomous agent

Bhargav Teja Nallapu 1 Frédéric Alexandre 1 
1 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
Abstract : Learning to survive in a complex environment is a more relevant task for the design of intelligent autonomous machines than complex problem solving. To establish this statement, we emphasize that autonomy requires emotional-and motivational-like characteristics that are much more straightforward to define in the context of survival tasks than in problem solving which is classically considered with intelligent agents. We also propose that using a simulation platform is a good preliminary step before the design of real machines because it allows to consider another fundamental challenge, related to the association of these emotional and motivational characteristics to higher cognitive functions. These considerations are illustrated by current simulations that we are carrying out with a bio-inspired neuronal model of the cerebral architecture of primates.
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Submitted on : Thursday, November 22, 2018 - 8:08:56 PM
Last modification on : Saturday, June 25, 2022 - 10:38:44 AM
Long-term archiving on: : Saturday, February 23, 2019 - 3:56:51 PM


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  • HAL Id : hal-01931573, version 1



Bhargav Teja Nallapu, Frédéric Alexandre. A survival task for the design and the assessment of an autonomous agent. 7th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2018, Jul 2018, Paris, France. ⟨hal-01931573⟩



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