Active Predictive Coding: A Unified Neural Framework for Learning Hierarchical World Models for Perception and Planning

An organizing principle for cerebral function: the unit model and the distributed system

Mountcastle, V. (1978) · 1978

Earlier work this paper cites.

Simple statistical gradient-following algorithms for connectionist reinforcement learning

Williams, R. J. (1992) · 1992

Earlier work this paper cites.

Planning and acting in partially observable stochastic domains

Kaelbling, L. P., Littman, M. L., and Cassandra, A. R. (1998) · 1998

Earlier work this paper cites.

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects

Rao, R. P. N. and Ballard, D. H. (1999) · 1999

Earlier work this paper cites.

Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning

Sutton, R. S., Precup, D., and Singh, S. (1999) · 1999

Earlier work this paper cites.

Policy gradient methods for reinforcement learning with function approximation

Sutton, R. S., McAllester, D., Singh, S., and Mansour, Y. (2000) · 2000

Earlier work this paper cites.

Robust constrained model predictive control

Richards, A. (2004) · 2004

Earlier work this paper cites.

Hierarchically organized behavior and its neural foundations: a reinforcement learning perspective

Botvinick, M. M., Niv, Y., and Barto, A. G. (2009) · 2009

Earlier work this paper cites.

Predictive coding under the free-energy principle

Friston, K. and Kiebel, S. (2009) · 2009

Earlier work this paper cites.

Decision making under uncertainty: a neural model based on partially observable markov decision processes

Rao, R. P. (2010) · 2010

Earlier work this paper cites.

Imagenet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., and Hinton, G. E. (2012) · 2012

Earlier work this paper cites.

Functional Connections of Cortical Areas: A New View from the Thalamus

Sherman, S. M. and Guillery, R. W. (2013) · 2013

Cited alongside, same era.

Recurrent models of visual attention

Mnih, V., Heess, N., Graves, A., and kavukcuoglu, k. (2014) · 2014

Cited alongside, same era.

Adam: A method for stochastic optimization

Kingma, D. P. and Ba, J. (2015) · 2015

Cited alongside, same era.

The option-critic architecture

Original

Bacon, P.-L., Harb, J., and Precup, D. (2016) · 2016

Cited alongside, same era.

Attend, infer, repeat: Fast scene understanding with generative models

Eslami, S. M. A., Heess, N., Weber, T., Tassa, Y., Szepesvari, D., kavukcuoglu, k., and Hinton, G. E. (2016) · 2016

Cited alongside, same era.

Hypernetworks

Ha, D., Dai, A. M., and Le, Q. V. (2017) · 2017

Stacked capsule autoencoders

Kosiorek, A., Sabour, S., Teh, Y. W., and Hinton, G. E. (2019) · 2019

Later among the works it cites.

Locations in the neocortex: A theory of sensorimotor object recognition using cortical grid cells

Lewis, M., Purdy, S., Ahmad, S., and Hawkins, J. (2019) · 2019

Later among the works it cites.

Principled weight initialization for hypernetworks

Chang, O., Flokas, L., and Lipson, H. (2020) · 2020

Later among the works it cites.

On the modularity of hypernetworks

Galanti, T. and Wolf, L. (2020) · 2020

Later among the works it cites.

Mastering atari with discrete world models

Hafner, D., Lillicrap, T., Norouzi, M., and Ba, J. (2021) · 2021

Later among the works it cites.

A Thousand Brains: A New Theory of Intelligence

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Later among the works it cites.