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Joel Lehman
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Abandoning objectives: Evolution through the search for novelty alone
J Lehman, KO Stanley
Evolutionary computation 19 (2), 189-223, 2011
12272011
An intriguing failing of convolutional neural networks and the coordconv solution
R Liu, J Lehman, P Molino, F Petroski Such, E Frank, A Sergeev, ...
Advances in neural information processing systems 31, 2018
10292018
Deep neuroevolution: Genetic algorithms are a competitive alternative for training deep neural networks for reinforcement learning
FP Such, V Madhavan, E Conti, J Lehman, KO Stanley, J Clune
arXiv preprint arXiv:1712.06567, 2017
9452017
Designing neural networks through neuroevolution
KO Stanley, J Clune, J Lehman, R Miikkulainen
Nature Machine Intelligence 1 (1), 24-35, 2019
7952019
Exploiting open-endedness to solve problems through the search for novelty.
J Lehman, KO Stanley
ALIFE, 329-336, 2008
7202008
Evolving a diversity of virtual creatures through novelty search and local competition
J Lehman, KO Stanley
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
5672011
Go-explore: a new approach for hard-exploration problems
A Ecoffet, J Huizinga, J Lehman, KO Stanley, J Clune
arXiv preprint arXiv:1901.10995, 2019
4552019
Improving exploration in evolution strategies for deep reinforcement learning via a population of novelty-seeking agents
E Conti, V Madhavan, F Petroski Such, J Lehman, K Stanley, J Clune
Advances in neural information processing systems 31, 2018
4282018
First return, then explore
A Ecoffet, J Huizinga, J Lehman, KO Stanley, J Clune
Nature 590 (7847), 580-586, 2021
4082021
The surprising creativity of digital evolution: A collection of anecdotes from the evolutionary computation and artificial life research communities
J Lehman, J Clune, D Misevic, C Adami, L Altenberg, J Beaulieu, ...
Artificial life 26 (2), 274-306, 2020
3642020
Paired open-ended trailblazer (poet): Endlessly generating increasingly complex and diverse learning environments and their solutions
R Wang, J Lehman, J Clune, KO Stanley
arXiv preprint arXiv:1901.01753, 2019
2722019
A neuroevolution approach to general atari game playing
M Hausknecht, J Lehman, R Miikkulainen, P Stone
IEEE Transactions on Computational Intelligence and AI in Games 6 (4), 355-366, 2014
2602014
Novelty search and the problem with objectives
J Lehman, KO Stanley
Genetic programming theory and practice IX, 37-56, 2011
2212011
Why greatness cannot be planned: The myth of the objective
KO Stanley, J Lehman
Springer, 2015
2002015
Learning to continually learn
S Beaulieu, L Frati, T Miconi, J Lehman, KO Stanley, J Clune, N Cheney
ECAI 2020, 992-1001, 2020
1912020
Generative teaching networks: Accelerating neural architecture search by learning to generate synthetic training data
FP Such, A Rawal, J Lehman, K Stanley, J Clune
International Conference on Machine Learning, 9206-9216, 2020
1882020
Revising the evolutionary computation abstraction: minimal criteria novelty search
J Lehman, KO Stanley
Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010
1582010
Efficiently evolving programs through the search for novelty
J Lehman, KO Stanley
Proceedings of the 12th annual conference on Genetic and evolutionary …, 2010
1542010
Enhanced poet: Open-ended reinforcement learning through unbounded invention of learning challenges and their solutions
R Wang, J Lehman, A Rawal, J Zhi, Y Li, J Clune, K Stanley
International conference on machine learning, 9940-9951, 2020
1282020
Safe mutations for deep and recurrent neural networks through output gradients
J Lehman, J Chen, J Clune, KO Stanley
Proceedings of the Genetic and Evolutionary Computation Conference, 117-124, 2018
1132018
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