Meta-learning within Projective Simulation

Meta-learning within Projective Simulation

Learning models of artificial intelligence can nowadays perform very well on a large variety of tasks. However, in practice, different task environments are best handled by different learning models, rather than a single universal approach. Most non-trivial models thus require the adjustment of seve...

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Bibliographic Details
Main Authors: Adi Makmal, Alexey A. Melnikov, Vedran Dunjko, Hans J. Briegel
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Machine learning
reinforcement learning
adaptive algorithm
meta-learning
random processes
quantum mechanics
Online Access:https://ieeexplore.ieee.org/document/7458793/

Internet

https://ieeexplore.ieee.org/document/7458793/

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