Notice bibliographique
- Notice
000 cam 22 3 450
001 FRBNF452207330000005
010 .. $a 978-0-262-03604-7 $b rel.
035 .. $a OCoLC960940230
100 .. $a 20170616d2017 m y0engy50 ba
101 0. $a eng
102 .. $a US
105 .. $a ||||z 00|||
106 .. $a r
181 .0 $6 01 $a i $b xxxe
181 .. $6 02 $c txt $2 rdacontent
182 .0 $6 01 $a n
182 .. $6 02 $c n $2 rdamedia
200 1. $a Common sense, the Turing test, and the quest for real AI $b Texte imprimé $f Hector J. Levesque
214 .0 $a Cambridge, Mass. $c MIT press
214 .4 $d C 2017
215 .. $a 1 vol. (XV-172 p.) $d 21 cm
300 .. $a Bibliogr. p. 157-167
327 1. $a What kind of AI? ; The big puzzle ; Knowledge and behavior ; Making it and faking
it ; Learning with and without experience ; Book smarts and street smarts ; The
long tail and the limits to training ; Symbols and symbol processing ; Knowledge-based
systems ; AI technology.
330 .. $a "What can artificial intelligence teach us about the mind? If AI's underlying concept
is that thinking is a computational process, then how can computation illuminate thinking?
It's a timely question. AI is all the rage, and the buzziest AI buzz surrounds adaptive
machine learning: computer systems that learn intelligent behavior from massive amounts
of data. This is what powers a driverless car, for example. In this book, Hector Levesque
shifts the conversation to good old fashioned artificial intelligence, which is based
not on heaps of data but on understanding commonsense intelligence. This kind of artificial
intelligence is equipped to handle situations that depart from previous patterns,
as we do in real life, when, for example, we encounter a washed-out bridge or when
the barista informs us there's no more soy milk. Levesque considers the role of language
in learning. He argues that a computer program that passes the famous Turing Test
could be a mindless zombie, and he proposes another way to test for intelligence --
the Winograd Schema Test, developed by Levesque and his colleagues. If our goal is
to understand intelligent behavior, we had better understand the difference between
making it and faking it, he observes. He identifies a possible mechanism behind common
sense and the capacity to call on background knowledge: the ability to represent objects
of thought symbolically. As AI migrates more and more into everyday life, we should
worry if systems without common sense are making decisions where common sense is needed."
-- Provided by publisher
676 .. $a 006.301 $v 23
801 .3 $a US $b OCoLC $c 20170616 $h 960940230 $2 marc21
801 .0 $b DLC $g rda
930 .. $5 FR-751131009:45220733001001 $a 006.3 LEVE c $b 759999999 $c Tolbiac - Rez de Jardin - Sciences et technique - Salle R - Libre accès $d N
