A Neuromorphic Architecture for Reinforcement Learning from Real-Valued Observations

The proposed network contains clustering layers, based on earlier work by Afshar et al., 2020 and Bethi et al., 2022, with an introduction of TD-error modulation and eligibility traces.

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Sérgio F. Chevtchenko, Yeshwanth Bethi, Teresa B. Ludermir, Saeed Afshar (2024). Dataset: A Neuromorphic Architecture for Reinforcement Learning from Real-Valued Observations. https://doi.org/10.57702/jtxgqg8w

DOI retrieved: December 16, 2024

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.2307.02947
Author Sérgio F. Chevtchenko
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Yeshwanth Bethi
Teresa B. Ludermir
Saeed Afshar