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pro vyhledávání: '"Lenchner, Jon"'
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Autor:
Ganapini, Marianna B., Campbell, Murray, Fabiano, Francesco, Horesh, Lior, Lenchner, Jon, Loreggia, Andrea, Mattei, Nicholas, Rahgooy, Taher, Rossi, Francesca, Srivastava, Biplav, Venable, Brent
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that existing cognitive theories of human decision making, such as the thi
Externí odkaz:
http://arxiv.org/abs/2201.07050
Autor:
Ganapini, Marianna Bergamaschi, Campbell, Murray, Fabiano, Francesco, Horesh, Lior, Lenchner, Jon, Loreggia, Andrea, Mattei, Nicholas, Rossi, Francesca, Srivastava, Biplav, Venable, Kristen Brent
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life. However, we are still mostly seeing instances of narrow AI: many of these recent developments are typically focused on a very limite
Externí odkaz:
http://arxiv.org/abs/2110.01834
Autor:
Booch, Grady, Fabiano, Francesco, Horesh, Lior, Kate, Kiran, Lenchner, Jon, Linck, Nick, Loreggia, Andrea, Murugesan, Keerthiram, Mattei, Nicholas, Rossi, Francesca, Srivastava, Biplav
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence 2021, 35(17), 15042-15046
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making. The premise is that if we gain insights about the causes of some human capabilities that are still lacking in AI (for ins
Externí odkaz:
http://arxiv.org/abs/2010.06002