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Treelets vs. semantic networks First, standard semantic networks are extremely vulnerable to what we might call the damaged-grandmother-node problem. If a single grandmother node is a physical part...
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1. ExternalSystemsThatCanRepresentRecursiveStructure two common external systems for representing recursive combinations, numbers, and sentences. Consider first the decimal number scheme. This syst...
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The idea that the mind represents explicit, recursive structured combinations of elements has been challenged in two related but distinct ways. 1. A geometrical conception: P. M. Churchland (1986) ...
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3 criteria for evaluating competing models: 1. a model should be able to add -ed freely to novel words, even those with unfamiliar sounds. 2. An adequate model should produce defaultlike effects ev...
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An alternative possibility of registers is temporal synchrony (dynamic binding). My own view is that temporal synchrony might well play a role in some aspects of vision, such as grouping of parts o...
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Memory? A limitation of the binding schemes discussed so far is that none pro- vides a way of storing a binding. The bindings that are created are all entirely transitory, commonly taken to be cons...
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proposed by Smolensky (1990) （大佬就在隔壁_(:_」∠)_ A tensor product is a way of representing a binding between a variable and an instance. A tensor product is not (by itself) a way of representi...
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Cases in which humans can freely generalize UQOTOM on the basis of restricted data are problematic for multiple-nodes-per-variable multi-layer perceptrons trained by back-propagation. But this does...
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As it happens, many models that allocate just one node per variable rely on continuously varying input nodes rather than binary input nodes (analog encoding), whereas models that use multiple nodes...
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Universally quantified one-toone-mappings (UQOTOM) Two particularly important functions that are both universally quantified and one-to-one are identity (f(x) = x) and concatention (f(x,y) = xy. Al...
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The trouble is that there are too many different ways of defining what is meant by a symbol. Advocates of symbol-manipulation assume that there is something analogous to external symbols (words, st...
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None of the preliminary considerations that apparently favor multilayer perceptions -- biological plausibility, universal function approximation, and the like -- is actually decisive. Instead, as i...
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Feedforward network Simple recurrent network (SRN): unlike feedforward network, SRN can learn something about sequences of elements presented over time. An example of feedforward network: Hinton's ...
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Most models are born with their weights initially set to random values. These weights are then adjusted by a learning algorithm on the basis of a series of training examples that pair inputs with t...
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Functions like AND and OR are easily represented in simple two-layer networs. many other functions cannot be represented so easily. For example, our simple network could not represent the functionn...
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Notes: units that have activation values, which in turn are simply numbers like 1.0 or 0.5. Input and output nodes also have meanings or labels that are assigned by an external programmer. The mean...
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hmmm Most people associate the term (connectionnism) with the researchers who have most directly challenged the symbol-manipulation hypothesis, but the field of connectionism also encompasses model...
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But I am not an anti-connectionist; I am opposed only to a particular subset of the possible connectionnist models. The problem is that the term connectionism has become synonymous with a sinngle k...
