+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Forward propagating reinforcement learning--biologically plausible learning method for multi-layer networks



Forward propagating reinforcement learning--biologically plausible learning method for multi-layer networks



Bio Systems 71(1-2): 213-220



We introduce a biologically plausible method of implementing reinforcement learning to multi-layer neural networks. The key idea is to spatially localize the synaptic modulation induced by reinforcement signals, proceeding downstream from the initial layer to the final layer. Since reinforcement signals are known to be broadcast signals in the actual brain, we need two key assumptions, inhibitory backward connections and bypass to output units, to spatially localize the effect of delayed reinforcement without breaking the basic laws of neurophysiology.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 049104883

Download citation: RISBibTeXText

PMID: 14568222

DOI: 10.1016/s0303-2647(03)00127-8


Related references

A biologically plausible computational model of meta learning in reinforcement learning. Society for Neuroscience Abstract Viewer & Itinerary Planner : Abstract No 283 20, 2002

Biologically plausible deep learning But how far can we go with shallow networks?. Neural Networks 118: 90-101, 2019

A more biologically plausible learning rule for neural networks. Proceedings of the National Academy of Sciences of the United States of America 88(10): 4433-4437, 1991

A Biologically Plausible Architecture of the Striatum to Solve Context-Dependent Reinforcement Learning Tasks. Frontiers in Neural Circuits 11: 45, 2017

Biologically plausible learning in neural networks with modulatory feedback. Neural Networks 88: 32-48, 2017

Biologically plausible learning in neural networks: a lesson from bacterial chemotaxis. Biological Cybernetics 101(5-6): 379-385, 2009

Biologically plausible learning rules for neural networks and quantum computing. Neurocomputing 32-33: 921-926, 2000

A biologically plausible learning rule for the Infomax on recurrent neural networks. Frontiers in Computational Neuroscience 8: 143, 2014

Comparing pfc neuronal activity with the model forward propagating reinforcement learning in the selective attention task. Society for Neuroscience Abstract Viewer & Itinerary Planner : Abstract No 280 7, 2002

A learning scheme of multi-layered neural network models by forward-propagating errors. Neuroscience Research Suppl. (24): S155, 2000

A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace. International Journal of Neural Systems 13(4): 215-223, 2003

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks. Elife 6:, 2017

Concept learning through deep reinforcement learning with memory-augmented neural networks. Neural Networks 110: 47-54, 2019

Learning styles' recognition in e-learning environments with feed-forward neural networks. Journal of Computer Assisted Learning 22(3): 197-206, 2006

A Cross-Layer Routing Protocol Based on Quasi-Cooperative Multi-Agent Learning for Multi-Hop Cognitive Radio Networks. Sensors 19(1):, 2019