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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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Cite this as

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

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Additional Info

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