A Procedural Constructive Learning Mechanism with Deep Reinforcement Learning for Cognitive Agents

Recent advancements in AI and deep learning have created a growing demand for artificial agents capable of performing tasks within increasingly complex environments. To address the challenges associated with continuous learning constraints and knowledge capacity in this context, cognitive architectu...

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Vydané v:	Journal of intelligent & robotic systems Ročník 110; číslo 1; s. 38
Hlavní autori:	de Lellis Rossi, Leonardo, Rohmer, Eric, Dornhofer Paro Costa, Paula, Colombini, Esther Luna, da Silva Simões, Alexandre, Gudwin, Ricardo Ribeiro
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dordrecht Springer Netherlands 01.03.2024 Springer Nature B.V
Predmet:	Agents (artificial intelligence) Algorithms Artificial Intelligence Cognition Cognitive tasks Control Deep learning Electrical Engineering Engineering Humanoid Knowledge acquisition Machine learning Mechanical Engineering Mechatronics Neural networks Regular Paper Robotics Task complexity Cognitive architecture Deep reinforcement learning Neural networks Developmental robotics
ISSN:	0921-0296, 1573-0409
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