Artificial Inteligence

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03 de março de 2011, 11:14 O encontro da genética com os bits, a fusão essencial. Por Ricardo Murer » Inteligência artificial, Watson e o último xeque-mate Webinsider » Inteligência artificial, Watson e o último xeque-mate Webinsider
Transderivational search Transderivational search Transderivational search (often abbreviated to TDS) is a psychological and cybernetics term, meaning when a search is being conducted for a fuzzy match across a broad field. In computing the equivalent function can be performed using content-addressable memory. A psychological example of TDS is in Ericksonian hypnotherapy, where vague suggestions are used that the patient must process intensely in order to find their own meanings, thus ensuring that the practitioner does not intrude his own beliefs into the subject's inner world.[citation needed] TDS in human communication and processing[edit]
Autoassociative memory, also known as auto-association memory or an autoassociation network, is often misunderstood to be only a form of backpropagation or other neural networks. It is actually a more generic term that refers to all memories that enable one to retrieve a piece of data from only a tiny sample of itself. Traditional memory stores data at a unique address and can recall the data upon presentation of the complete unique address. Autoassociative memories are capable of retrieving a piece of data upon presentation of only partial information from that piece of data. Heteroassociative memories, on the other hand, can recall an associated piece of datum from one category upon presentation of data from another category. Autoassociative memory Autoassociative memory
A Hopfield network is a form of recurrent artificial neural network invented by John Hopfield in 1982. Hopfield nets serve as content-addressable memory systems with binary threshold nodes. They are guaranteed to converge to a local minimum, but convergence to a false pattern (wrong local minimum) rather than the stored pattern (expected local minimum) can occur. Hopfield net Hopfield net
Bidirectional associative memory Bidirectional associative memory Topology[edit] A BAM contains two layers of neurons, which we shall denote X and Y. Layers X and Y are fully connected to each other. Once the weights have been established, input into layer X presents the pattern in layer Y, and vice versa. Procedure[edit]
Researchers have offered several possible explanations of the spacing effect, and much research has been conducted that supports its impact on recall. In spite of these findings, the robustness of this phenomenon and its resistance to experimental manipulation have made empirical testing of its parameters difficult. Causes for spacing effect[edit] Decades of research on memory and recall have produced many different theories and findings on the spacing effect. In a study conducted by Cepeda et al. (2006) participants who used spaced practice on memory tasks outperformed those using massed practice in 259 out of 271 cases. Spacing effect Spacing effect
Interference theory Interference theory Interference theory is theory regarding human memory. Interference occurs in learning when there is an interaction between the new material and transfer effects of past learned behavior, memories or thoughts that have a negative influence in comprehending the new material.[1] Bringing to memory old knowledge has the effect of impairing both the speed of learning and memory performance. There are two main kinds of interference: proactive interference [see Proactive learning]retroactive interference [see Retroactive learning] The main assumption of interference theory is that the stored memory is intact but unable to be retrieved due to competition created by newly acquired information.[1]
Semantic reasoner Semantic reasoner A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining.
Intelligent agent Intelligent agent Simple reflex agent Intelligent agents are often described schematically as an abstract functional system similar to a computer program. For this reason, intelligent agents are sometimes called abstract intelligent agents (AIA)[citation needed] to distinguish them from their real world implementations as computer systems, biological systems, or organizations. Some definitions of intelligent agents emphasize their autonomy, and so prefer the term autonomous intelligent agents.