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Inductive biases of neural networks for generalization in spatial navigation

View ORCID ProfileRuiyi Zhang, View ORCID ProfileXaq Pitkow, Dora E Angelaki
doi: https://doi.org/10.1101/2022.12.07.519515
Ruiyi Zhang
1Department of Mechanical and Aerospace Engineering, New York University
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  • For correspondence: rz31@nyu.edu
Xaq Pitkow
3Department of Neuroscience, Baylor College of Medicine
4Department of Electrical and Computer Engineering, Rice University
5Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine
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Dora E Angelaki
1Department of Mechanical and Aerospace Engineering, New York University
2Center for Neural Science, New York University
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Abstract

Artificial reinforcement learning agents that perform well in training tasks typically perform worse than animals in novel tasks. We propose one reason: generalization requires modular architectures like the brain. We trained deep reinforcement learning agents using neural architectures with various degrees of modularity in a partially observable navigation task. We found that highly modular architectures that largely separate computations of internal belief of state from action and value allow better generalization performance than agents with less modular architectures. Furthermore, the modular agent’s internal belief is formed by combining prediction and observation, weighted by their relative uncertainty, suggesting that networks learn a Kalman filter-like belief update rule. Therefore, smaller uncertainties in observation than in prediction lead to better generalization to tasks with novel observable dynamics. These results exemplify the rationale of the brain’s inductive biases and show how insights from neuroscience can inspire the development of artificial systems with better generalization.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted December 07, 2022.
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Inductive biases of neural networks for generalization in spatial navigation
Ruiyi Zhang, Xaq Pitkow, Dora E Angelaki
bioRxiv 2022.12.07.519515; doi: https://doi.org/10.1101/2022.12.07.519515
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Inductive biases of neural networks for generalization in spatial navigation
Ruiyi Zhang, Xaq Pitkow, Dora E Angelaki
bioRxiv 2022.12.07.519515; doi: https://doi.org/10.1101/2022.12.07.519515

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