Term
artificial intelligence (AI)
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| A branch of computer science that investigates the extent to which machines can simulate or duplicate the intelligent behaviour of living organisms |
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| Neural networks that are programmed to learn by systematically reducing the discrepancy between their output and some desired output represented by a model or "teacher." Such systems learn by corrective feedback instead of by applying Hebb's rule. |
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| a multidiscipline approach to studying cognition in humans, animals, and machines. |
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Hebb's contention that neurons within the brain that are simultaneously or successively active become associated. One type of neural network applies this rule by adjusting the mathematical weights of units that are simultaneously or successively active. The result is that consistent input gradually produces consistent output. |
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| Information-processing Psychology |
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| The approach to studying cognition that follows in the tradition of faculty psychology and methodological (meditational) behaviourism and typically employs the computer as a model for human information processing. |
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| Did pioneering research on information-processing in the 1950s and 60s that significantly enhanced the popularity of cognitive psychology. |
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| A system of input, hidden, and output units that is capable of learning if the mathematical weights among the units are systematically modified either according to Hebb's rule or by back-propagation. |
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The most recent type of AI that utilizes artificial systems of neurons called neural networks. As contrasted with GOFAI, which employed the sequential processing of information according to specified rules, new connectionism employs the brain as a model. That is, the processing of information within a neural network is distributed throughout the entire network. Like the brain, neural networks are capable of learning, this was not true of GOFAI. |
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With his famous "Chinese Room" thought experiment sought to demonstrate that computer programs can simulate human thought processes but not duplicate them. Computer programs, he says, can only manipulate symbols according to rules (syntax) whereas humans assign meaning to symbols (semantics). Therefore, he accepts weak artificial intelligence and rejects strong artificial intelligence. |
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| Strong Artificial Intelligence |
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Definition
| The contention that machines (such as computers) can duplicate human cognitive processes. |
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| A test devised by Turing (1950) to determine whether a machine can think. Questions are submitted to both a human and a machine. If the machine's answers are indistinguishable from those of the human, it is concluded that the machine can think. |
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Term
| weak artificial intelligence |
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Definition
| the contention that machines (such as computers) can simulate human cognitive processes but not duplicate them. |
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