2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.AI2023★ 1 cited
Comparing Reinforcement Learning and Human Learning using the Game of Hidden Rules
Eric Pulick, Vladimir Menkov, Yonatan Mintz +2
Reliable real-world deployment of reinforcement learning (RL) methods requires a nuanced understanding of their strengths and weaknesses and how they compare to those of humans. Hu…
cs.LG2022★ 2 cited
The Game of Hidden Rules: A New Kind of Benchmark Challenge for Machine Learning
Eric Pulick, Shubham Bharti, Yiding Chen +4
As machine learning (ML) is more tightly woven into society, it is imperative that we better characterize ML's strengths and limitations if we are to employ it responsibly. Existin…
cs.LG2019
Can We Distinguish Machine Learning from Human Learning?
Vicki Bier, Paul B. Kantor, Gary Lupyan +1
What makes a task relatively more or less difficult for a machine compared to a human? Much AI/ML research has focused on expanding the range of tasks that machines can do, with a…