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Organisms in nature have evolved to exhibit flexibility in face of changes to the environment and/or to themselves.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 1901
Earlier work this paper cites.
Neuronlike adaptive elements that can solve difficult learning control problems
Andrew G Barto, Richard S Sutton, and Charles W Anderson. 1983 · 1983
Earlier work this paper cites.
Efficient memory-based learning for robot control
Andrew William Moore. 1990 · 1990
Earlier work this paper cites.
The evolution of learning: An experiment in genetic connectionism
David J Chalmers. 1991 · 1991
Earlier work this paper cites.
Approximation capabilities of multilayer feedforward networks
Kurt Hornik. 1991 · 1991
Earlier work this paper cites.
Generalization in reinforcement learning: Successful examples using sparse coarse coding
Richard S Sutton. 1995 · 1995
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Synaptic plasticity: taming the beast
Larry F Abbott and Sacha B Nelson. 2000 · 2000
Earlier work this paper cites.
Spike timing-dependent plasticity of neural circuits
Yang Dan and Mu-ming Poo. 2004 · 2004
Earlier work this paper cites.
Evolving plastic neural networks for online learning: review and future directions. In Australasian Joint Conference on Artificial Intelligence . Springer, 326–337
Oliver J Coleman and Alan D Blair. 2012 · 2012
Earlier work this paper cites.
Twenty-five lessons from computational neuromodulation
Peter Dayan. 2012 · 2012
Earlier work this paper cites.
Biological psychology: An introduction to behavioral, cognitive, and clinical neuroscience
S Marc Breedlove and Neil V Watson. 2013 · 2013
Earlier work this paper cites.
On the properties of neural machine translation: Encoder-decoder approaches
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Artificial evolution of plastic neural networks: a few key concepts
Jean-Baptiste Mouret and Paul Tonelli. 2014 · 2014
Cited alongside, same era.
Deep learning in neural networks: An overview
Jürgen Schmidhuber. 2015 · 2015
Cited alongside, same era.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba. 2016 · 2016
Cited alongside, same era.
A brief survey of deep reinforcement learning
Kai Arulkumaran, Marc Peter Deisenroth, Miles Brundage, and Anil Anthony Bharath. 2017 · 2017
Cited alongside, same era.
A review of recurrent neural networks: LSTM cells and network architectures
Yong Yu, Xiaosheng Si, Changhua Hu, and Jianxun Zhang. 2019 · 2019
Later among the works it cites.
Network of evolvable neural units can learn synaptic learning rules and spiking dynamics
Paul Bertens and Seong-Whan Lee. 2020 · 2020
Later among the works it cites.
On the binding problem in artificial neural networks
Klaus Greff, Sjoerd van Steenkiste, and Jürgen Schmidhuber. 2020 · 2020
Later among the works it cites.
EvoStrat
Rasmus Berg Palm. 2020 · 2020
Later among the works it cites.
Testing the genomic bottleneck hypothesis in Hebbian meta-learning. In NeurIPS 2020 Workshop on Pre-registration in Machine Learning . PMLR, 100–110
Rasmus Berg Palm, Elias Najarro, and Sebastian Risi. 2021 · 2020
Later among the works it cites.
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Evolving Stable Strategies
David Ha. 2017 · 2017
Cited alongside, same era.
Evolution strategies as a scalable alternative to reinforcement learning
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, and Ilya Sutskever. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Cited alongside, same era.
Born to learn: the inspiration, progress, and future of evolved plastic artificial neural networks
Andrea Soltoggio, Kenneth O Stanley, and Sebastian Risi. 2018 · 2018
Cited alongside, same era.
Improving deep learning with generic data augmentation. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI) . IEEE, 1542–1547
Luke Taylor and Geoff Nitschke. 2018 · 2018
Cited alongside, same era.
The super-learning hypothesis: Integrating learning processes across cortex, cerebellum and basal ganglia
Daniele Caligiore, Michael A Arbib, R Chris Miall, and Gianluca Baldassarre. 2019 · 2019
Cited alongside, same era.
Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch. 2021 · 2021
Later among the works it cites.
Introducing Symmetries to Black Box Meta Reinforcement Learning
Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram Friesen, Junhyuk Oh, and Yutian Chen. 2021 · 2021
Later among the works it cites.
Joachim Winther Pedersen and Sebastian Risi. 2021 · 2021
Later among the works it cites.
Linear Transformers are secretly fast weight programmers. In International Conference on Machine Learning . PMLR, 9355–9366
Imanol Schlag, Kazuki Irie, and Jürgen Schmidhuber. 2021 · 2021
Later among the works it cites.
The sensory neuron as a transformer: Permutation-invariant neural networks for reinforcement learning
Yujin Tang and David Ha. 2021 · 2021
Later among the works it cites.
Evolving plasticity for autonomous learning under changing environmental conditions
Anil Yaman, Giovanni Iacca, Decebal Constantin Mocanu, Matt Coler, George Fletcher, and Mykola Pechenizkiy. 2021 · 2021
Later among the works it cites.
MetaMorph: Learning Universal Controllers with Transformers
Agrim Gupta, Linxi Fan, Surya Ganguli, and Li Fei-Fei. 2022 · 2022
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