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pro vyhledávání: '"Lokendra Shastri"'
Autor:
Lokendra Shastri
Publikováno v:
Metascience. 29:283-287
Publikováno v:
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society ISBN: 9781410603494
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society
Proceedings of the Twenty First Annual Conference of the Cognitive Science Society
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ca32acd871aed8c342ee70b162cf567
https://doi.org/10.4324/9781410603494-3
https://doi.org/10.4324/9781410603494-3
Autor:
Lokendra Shastri
Publikováno v:
Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society ISBN: 9781315782379
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61705dd0cdf07b8ba7ad52b474fa4fc4
https://doi.org/10.4324/9781315782379-41
https://doi.org/10.4324/9781315782379-41
Autor:
Carter Wendelken, Lokendra Shastri
Publikováno v:
Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society ISBN: 9781315782379
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aaa0d52a3fd54d1e074572a26df841a1
https://doi.org/10.4324/9781315782379-194
https://doi.org/10.4324/9781315782379-194
Publikováno v:
AI Magazine; Vol 36, No 2: Summer 2015; 3-9
This editorial to the summer 2015 AI Magazine introduces the special-issue articles on architectures for activity recognition and context-aware computing.
Sentiment Extraction: Integrating Statistical Parsing, Semantic Analysis, and Common Sense Reasoning
Publikováno v:
IAAI
Much of the ongoing explosion of digital content is in the form of text. This content is a virtual gold-mine of information that can inform a range of social, governmental, and business decisions. For example, using content available on blogs and soc
Autor:
Carter Wendelken, Lokendra Shastri
Publikováno v:
Connection Science. 16:211-217
The SHRUTI model demonstrates how a neurally motivated connectionist architecture can support encoding of complex evidential and relational knowledge and perform rapid inference and decision-making with that knowledge. Key to the successful operation
Autor:
Lokendra Shastri, Carter Wendelken
Publikováno v:
Neurocomputing. :363-370
SHRUTI is a connectionist model that demonstrates how a network of neuron-like elements can encode a large body of semantic, episodic, and causal knowledge, and rapidly make decisions and perform explanatory and predictive reasoning. To further groun
Autor:
Lokendra Shastri
Publikováno v:
Neurocomputing. :33-41
A computational abstraction of long-term potentiation (LTP) is proposed. The abstraction captures key temporal and cooperative properties of LTP, and also lends itself to rapid computation. The abstraction is used to simulate the recruitment of bindi
Autor:
Lokendra Shastri
Publikováno v:
Trends in Cognitive Sciences. 6:162-168
There is a broad consensus that the hippocampal system plays a critical role in the encoding and retrieval of 'episodic' memories. Recent findings and computational modeling explicate the representational requirements of encoding episodic memories, a