Reinforcement Learning on Slow Features of High-Dimensional Input Streams-Reference-Cited by-同舟云学术

Reinforcement Learning on Slow Features of High-Dimensional Input Streams

Published:2010-08-19 Issue:8 Volume:6 Page:e1000894
ISSN:1553-7358
Container-title:PLoS Computational Biology
language:en
Short-container-title:PLoS Comput Biol

Author:

Legenstein Robert,Wilbert Niko,Wiskott Laurenz

Publisher

Public Library of Science (PLoS)

Subject

Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modelling and Simulation,Ecology, Evolution, Behavior and Systematics

Reference60 articles.

1. Animal Intelligence;E Thorndike,1911

2. Neuro-Dynamic Programming;DP Bertsekas,1996

3. Reinforcement Learning: An Introduction;RS Sutton,1998

4. A neural substrate of prediction and reward.;W Schultz;Science,1997

5. Dopamine-dependent plasticity of corticostriatal synapses.;JN Reynolds;Neural Netw,2002

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An inductive bias for slowly changing features in human reinforcement learning;2024-01-24

2. Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison;Lecture Notes in Computer Science;2024

3. Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning;Cognitive Computation;2023-01-20

4. A latent feature oriented dictionary learning method for closed-loop process monitoring;ISA Transactions;2022-12

5. Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning;2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2022-10-23