Spiking neural controllers in multi-agent competitive systems for adaptive targeted motor learning

DOI10.1016/J.JFRANKLIN.2015.04.014zbMath1395.93308OpenAlexW253082682MaRDI QIDQ1660567

Alessandra Vitanza, Paolo Arena, Luca Patané

Publication date: 16 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2015.04.014

zbMATH Keywords

adaptive targeted motor learningmulti-agent competitive systemsspiking neural controllers

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Feedback control (93B52) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Artificial intelligence for robotics (68T40) Agent technology and artificial intelligence (68T42)

Related Items (2)

Pre-processing and transfer entropy measures in motor neurons controlling limb movements ⋮ Distributed observer-based cooperative guidance with appointed impact time and collision avoidance

Cites Work

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• A Mathematical Theory of Communication
• A Universal Model for Spike-Frequency Adaptation
• Measurement of Diversity

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