Artificial Intelligence

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categorie: Engleza

nota: 9.75

nivel: Facultate

Artificial Intelligence
Since we do not find computational systems in the natural world, it is more safe to presume that human thinking is only like computational processes. Third, human cognition seems to involves a global understanding of one's environment, and this is not so of computational processes.

Given these problems, critics contend that human thinking seems to be [...]
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Artificial Intelligence
Since we do not find computational systems in the natural world, it is more safe to presume that human thinking is only like computational processes. Third, human cognition seems to involves a global understanding of one's environment, and this is not so of computational processes.

Given these problems, critics contend that human thinking seems to be functionally different than digital or serial programming.
The other school of strong AI is connectionism which contends that cognition is distributed across a number of neural nets, or interconnective nodes. On this view, there is no central processing unit, symbols are not as important, and information is diverse and redundant.

Artificial Intelligence
Perhaps most importantly, it is consistent with what we know about neurological arrangement. Unlike computational devices, devices made in the neural net fashion can execute commonsense tasks, recognize patterns efficiently, and learn. For example, by presenting a device with a series of male and female pictures, the device picks up on patterns and can correctly identify new pictures as male or female. In spite of these advantages, several criticisms have been launched against connectionism.

First, in teaching the device to recognize patterns, it takes too many training sessions, sometimes numbering in the thousands. Human children, by contrast, learn to recognize some patterns after a single exposure. Second, critics point out that neural net devices are not good at rule-based processing higher level reasoning, such as learning language.

These tasks are better accomplished by symbolic computation in serial computers. A third criticism is offered by Fodor who maintains that connectionism is presented with a dilemma concerning mental representation;
1.Mental representation is cognitive
2.If it is cognitive, then it is systematic (e.g., picking out one color or shape over another)
3.If it is systematic, then it is syntactic, like language, and consequently, it is algorithmic
4.However, if it is syntactic, then it is just the same old computationalism
5.If it is not syntactic, then it is not true cognition

But connectionists may defend themselves against Fodor's attack in at least two ways. First, they may object to premise two and claim that cognitive representation is not systematic, but, instead, is pictorial or holistic. Second, connectionists can point out that the same dilemma applies to human cognition. Since, presumably, we would want to deny (4) and (5) as pertains to humans, then we must reject the reasoning that leads to it.
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