Five Dimensions of Reasoning in the Wild
By D. Perlis. 2016
5 citations recorded by the source corpus.
Reasoning does not work well when done in isolation from its significance, both to the needs and interests of an agent and with respect to the wider world. Moreover, those issues may best be handled with a new sort of data structure that goes beyond the knowledge base and incorporates aspects of perceptual knowledge and even more, in which a kind of anticipatory action may be key.
Subfields: Artificial Intelligence, Cognitive Neuroscience, Management Science and Operations Research, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yejin Choi
- Mohit Bansal
- Luke S. Zettlemoyer
- Percy Liang
- Jacob Andreas
- Graham Neubig
- Jianfeng Gao
- Kyunghyun Cho
In Cognitive Neuroscience
- Joyce Yue Chai
- Mirella Lapata
- Yoshua Bengio
- Jacob Andreas
- Nicolas Pinto
- Yonatan Bisk
- Yann LeCun
- James J. DiCarlo
In Management Science and Operations Research
- Ari Holtzman
- Joseph P. Turian
- Mirella Lapata
- Yoshua Bengio
- Jacob Andreas
- Jesse Thomason
- Angeliki Lazaridou
- Yonatan Bisk
In Natural Language Processing
- Mohit Bansal
- Yejin Choi
- Graham Neubig
- Mirella Lapata
- Richard Socher
- Jacob Andreas
- Luke S. Zettlemoyer
- Christopher D. Manning
Citations in the corpus
- Experience Grounds Language (2020, background): “Models must be able to watch and recognize objects, people, and activities to understand the language describing them (Li et al., 2019b; Krishna et al., 2017; Yatskar et al., 2016; Perlis, 2016) and access fine-grained notions”