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20132026
most citedDeep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

544 citations · 1.7k across the 27 of their papers we have counts for

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Showing 2023Show all

3 papers · 1 filter

cs.AI2023★ 4 cited

OMNI: Open-endedness via Models of human Notions of Interestingness

Jenny Zhang, Joel Lehman, Kenneth Stanley +1

Open-ended algorithms aim to learn new, interesting behaviors forever. That requires a vast environment search space, but there are thus infinitely many possible tasks. Even after…

cs.AI2023★ 2 cited

Machine Love

Joel Lehman

While ML generates much economic value, many of us have problematic relationships with social media and other ML-powered applications. One reason is that ML often optimizes for wha…

cs.NE2023★ 63 cited

Language Model Crossover: Variation through Few-Shot Prompting

Elliot Meyerson, Mark J. Nelson, Herbie Bradley +4

This paper pursues the insight that language models naturally enable an intelligent variation operator similar in spirit to evolutionary crossover. In particular, language models o…