About: Neats and scruffies

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Neat and scruffy are two contrasting approaches to artificial intelligence (AI) research. The distinction was made in the 70s and was a subject of discussion until the middle 80s. In the 1990s and 21st century AI research adopted "neat" approaches almost exclusively and these have proven to be the most successful. "Neats" use algorithms based on formal paradigms such as logic, mathematical optimization or neural networks. Neat researchers and analysts have expressed the hope that a single formal paradigm can be extended and improved to achieve general intelligence and superintelligence.

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rdfs:label	Neats and scruffies (en)
rdfs:comment	Neat and scruffy are two contrasting approaches to artificial intelligence (AI) research. The distinction was made in the 70s and was a subject of discussion until the middle 80s. In the 1990s and 21st century AI research adopted "neat" approaches almost exclusively and these have proven to be the most successful. "Neats" use algorithms based on formal paradigms such as logic, mathematical optimization or neural networks. Neat researchers and analysts have expressed the hope that a single formal paradigm can be extended and improved to achieve general intelligence and superintelligence. (en)
dcterms:subject	Artificial intelligence Philosophy of artificial intelligence
Wikipage page ID	404037 (xsd:integer)
Wikipage revision ID	1061595295 (xsd:integer)
Link from a Wikipage to another Wikipage	Carnegie Mellon University Rodney Brooks Roger Schank Natural language processing History of artificial intelligence Joseph Weizenbaum Judea Pearl Peter Norvig Robert Kowalski University of Edinburgh Douglas Lenat ELIZA Intelligent agent Shakey the robot Artificial intelligence Mathematical optimization SRI International Optimization (mathematics) Edward Feigenbaum Logic MIT Machine learning Stanford Stuart J. Russell Commonsense knowledge (artificial intelligence) Computer vision Embodied cognition Planner programming language Planning Allen Newell Cyc Pamela McCorduck Hand coding Knowledge engineering Herbert A. Simon Attention Terry Winograd Artificial general intelligence Artificial intelligence Association for the Advancement of Artificial Intelligence Philosophy of artificial intelligence John Brockman (literary agent) John McCarthy (computer scientist) Edge detection Modularity SHRDLU Donald Michie Marvin Minsky Philosophy of artificial intelligence Free energy principle Intelligence Mind Semantic networks Superintelligence Karl Friston Soft computing Nils Nilsson (researcher) Neural networks Fast, Cheap and Out of Control Symbolic AI The Society of Mind dbr:Wikt:magic_bullet
Link from a Wikipage to an external page	https://archive.org/details/societyofmind00marv https://www.edge.org/conversation/information-is-surprises https://www.amazon.com/exec/obidos/ASIN/0684823446/qid=913732847/sr=1-3/002-6796862-3062667 https://www.taylorfrancis.com/books/edit/10.4324/9780203773574/beliefs-reasoning-decision-making-roger-schank-ellen-langer
sameAs	Neats and scruffies Neats and scruffies
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has abstract	Neat and scruffy are two contrasting approaches to artificial intelligence (AI) research. The distinction was made in the 70s and was a subject of discussion until the middle 80s. In the 1990s and 21st century AI research adopted "neat" approaches almost exclusively and these have proven to be the most successful. "Neats" use algorithms based on formal paradigms such as logic, mathematical optimization or neural networks. Neat researchers and analysts have expressed the hope that a single formal paradigm can be extended and improved to achieve general intelligence and superintelligence. "Scruffies" use any number of different algorithms and methods to achieve intelligent behavior. Scruffy programs may require large amounts of hand coding or knowledge engineering. Scruffies have argued that the general intelligence can only be implemented by solving a large number of essentially unrelated problems, and that there is no magic bullet that will allow programs to develop general intelligence autonomously. The neat approach is similar to physics, in that it uses simple mathematical models as its foundation. The scruffy approach is more like biology, where much of the work involves studying and categorizing diverse phenomena. (en)
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page length (characters) of wiki page	12617 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Neats_and_scruffies
is Link from a Wikipage to another Wikipage of	Neats vs. scruffies Artificial intelligence Symbolic artificial intelligence Outline of artificial intelligence Neat AI Neats Scruffies Scruffy AI
is Wikipage redirect of	Neats vs. scruffies

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