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Deep Multi-Agent Reinforcement Learning

Jakob N. Foerster : https://ora.ox.ac.uk/objects/uuid:a55621b3-53c0-4e1b-ad1c-92438b57ffa4
HYPE: A Benchmark for Human eYe Perceptual Evaluation of Generative Models

Human evaluation for generative models have been ad-hoc.

They propose a standard human benchmark for generative realism that is grounded in psychophysics research in perception.

https://arxiv.org/abs/1904.01121
https://hype.stanford.edu/
CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases
Yu et al.: https://arxiv.org/abs/1909.05378
#ArtificialIntelligence #Database #MachineLearning
Stanford Machine Learning Notes
Andrew Ng
https://www.holehouse.org/mlclass/
Since "2001: A Space Odyssey," people have wondered: could machines like HAL 9000 eventually exist that can process information with human-like intelligence?
Researchers at Michigan State University say that true, human-level intelligence remains a long way off, but their new paper published in The American Naturalist explores how computers could begin to evolve learning in the same way as natural organisms did—with implications for many fields, including artificial intelligence.

https://phys.org/news/2019-09-evolution-key-artificial-intelligence.html