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| 2. |  | VERRUMA, A. A.; MARTINELLI, P. R. P.; RABELLO, L. M.; INAMASU, R. Y.; BERNARDI, A. C. C. Uso de ferramentas de agricultura de precisão para controle de plantas daninhas e estimativas do custo de produção de cana-de-açúcar. In: SIMPÓSIO NACIONAL DE INSTRUMENTAÇÃO AGROPECUÁRIA, 2014, São Carlos, SP Anais do SIAGRO: ciência, inovação e mercado 2014. São Carlos, SP: Embrapa Instrumentação, 2014. p. 77-80. Editores: Carlos Manoel Pedro Vaz, Débora Marcondes Bastos Pereira Milori, Silvio Crestana.| Biblioteca(s): Embrapa Instrumentação; Embrapa Pecuária Sudeste. |
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| 3. | | VERRUMA, A. A.; MARTINELLI, P. R. P.; RABELLO, L. M.; INAMASU, R. Y.; SANTOS, K. E. L.; BETTIOL, G. M.; BERNARDI, A. C. de C. Soil and weed occurrence mapping and estimates of sugarcane production cost. Brazilian Journal of Biosystems Engineering, v. 11, n. 1, p. 68-78, 2017.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
|
Data corrente: |
29/10/2013 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 2 |
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Autoria: |
CASTRO, A. de. |
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Afiliação: |
ALEXANDRE DE CASTRO, CNPTIA. |
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Título: |
The thermodynamic cost of fast thought. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
Minds and Machines, Dordrecht, v. 23, n. 4, p. 473-487, Nov. 2013. |
|
DOI: |
10.1007/s11023-013-9302-x |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract After more than 60 years, Shannon's research continues to raise fundamental questions, such as the one formulated by R. Luce, which is still unanswered: "Why is information theory not very applicable to psychological problems, despite apparent similarities of concepts"? On this topic, S. Pinker, one of the foremost defenders of the widespread computational theory of mind, has argued that thought is simply a type of computation, and that the gap between human cognition and computational models may be illusory. In this context, in his latest book, titled Thinking Fast and Slow, D. Kahneman provides further theoretical interpretation by differentiating the two assumed systems of the cognitive functioning of the human mind. He calls them intuition (system 1) determined to be an associative (automatic, fast and perceptual) machine, and reasoning (system 2) required to be voluntary and to operate logical-deductively. In this paper, we propose a mathematical approach inspired by Ausubel's meaningful learning theory for investigating, from the constructivist perspective, information processing in the working memory of cognizers. Specifically, a thought experiment is performed utilizing the mind of a dual-natured creature known as Maxwell's demon: a tiny "man-machine" solely equipped with the characteristics of system 1, which prevents it from reasoning. The calculation presented here shows that the Ausubelian learning schema, when inserted into the creature's memory, leads to a Shannon-Hartley-like model that, in turn, converges exactly to the fundamental thermodynamic principle of computation, known as the Landauer limit. This result indicates that when the system 2 is shut down, both an intelligent being, as well as a binary machine, incur the same minimum energy cost per unit of information (knowledge) processed (acquired), which mathematically shows the computational attribute of the system 1, as Kahneman theorized. This finding links information theory to human psychological features and opens the possibility to experimentally test the computational theory of mind by means of Landauer's energy cost, which can pave a way toward the conception of a multi-bit reasoning machine. MenosAbstract After more than 60 years, Shannon's research continues to raise fundamental questions, such as the one formulated by R. Luce, which is still unanswered: "Why is information theory not very applicable to psychological problems, despite apparent similarities of concepts"? On this topic, S. Pinker, one of the foremost defenders of the widespread computational theory of mind, has argued that thought is simply a type of computation, and that the gap between human cognition and computational models may be illusory. In this context, in his latest book, titled Thinking Fast and Slow, D. Kahneman provides further theoretical interpretation by differentiating the two assumed systems of the cognitive functioning of the human mind. He calls them intuition (system 1) determined to be an associative (automatic, fast and perceptual) machine, and reasoning (system 2) required to be voluntary and to operate logical-deductively. In this paper, we propose a mathematical approach inspired by Ausubel's meaningful learning theory for investigating, from the constructivist perspective, information processing in the working memory of cognizers. Specifically, a thought experiment is performed utilizing the mind of a dual-natured creature known as Maxwell's demon: a tiny "man-machine" solely equipped with the characteristics of system 1, which prevents it from reasoning. The calculation presented here shows that the Ausubelian learning schema, when inserted into the creature's memory, leads ... Mostrar Tudo |
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Palavras-Chave: |
Cognitive structure; Computacionalismo; Computationalism; Demônio de Maxwell; Estrutura cognitiva; Limite de Landauer; Modelo Shannon-Hartley; Teoria do aprendizado de Ausubel. |
|
Thesaurus NAL: |
Cognition. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
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001 1969617
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024 7 $a10.1007/s11023-013-9302-x$2DOI
100 1 $aCASTRO, A. de
245 $aThe thermodynamic cost of fast thought.$h[electronic resource]
260 $c2013
520 $aAbstract After more than 60 years, Shannon's research continues to raise fundamental questions, such as the one formulated by R. Luce, which is still unanswered: "Why is information theory not very applicable to psychological problems, despite apparent similarities of concepts"? On this topic, S. Pinker, one of the foremost defenders of the widespread computational theory of mind, has argued that thought is simply a type of computation, and that the gap between human cognition and computational models may be illusory. In this context, in his latest book, titled Thinking Fast and Slow, D. Kahneman provides further theoretical interpretation by differentiating the two assumed systems of the cognitive functioning of the human mind. He calls them intuition (system 1) determined to be an associative (automatic, fast and perceptual) machine, and reasoning (system 2) required to be voluntary and to operate logical-deductively. In this paper, we propose a mathematical approach inspired by Ausubel's meaningful learning theory for investigating, from the constructivist perspective, information processing in the working memory of cognizers. Specifically, a thought experiment is performed utilizing the mind of a dual-natured creature known as Maxwell's demon: a tiny "man-machine" solely equipped with the characteristics of system 1, which prevents it from reasoning. The calculation presented here shows that the Ausubelian learning schema, when inserted into the creature's memory, leads to a Shannon-Hartley-like model that, in turn, converges exactly to the fundamental thermodynamic principle of computation, known as the Landauer limit. This result indicates that when the system 2 is shut down, both an intelligent being, as well as a binary machine, incur the same minimum energy cost per unit of information (knowledge) processed (acquired), which mathematically shows the computational attribute of the system 1, as Kahneman theorized. This finding links information theory to human psychological features and opens the possibility to experimentally test the computational theory of mind by means of Landauer's energy cost, which can pave a way toward the conception of a multi-bit reasoning machine.
650 $aCognition
653 $aCognitive structure
653 $aComputacionalismo
653 $aComputationalism
653 $aDemônio de Maxwell
653 $aEstrutura cognitiva
653 $aLimite de Landauer
653 $aModelo Shannon-Hartley
653 $aTeoria do aprendizado de Ausubel
773 $tMinds and Machines, Dordrecht$gv. 23, n. 4, p. 473-487, Nov. 2013.
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