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31 Cards in this Set
- Front
- Back
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Cartesian philosophy dualism |
* notion of the disembodied mind- the mind is separate from the body * the mind is a thinking thing that is separate from the physical, which does not thinking * the mind is infinite, separating it from the finite physical * however, a finite physical mechanism can create infinite variety. This is the core idea of classical cognitive science |
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recursion recursive rule system |
* permits finite operators to generate infinite variety * a function is recursive when it operates by referring to itself * for example, the successor function in arithmetic or the sierpinski triangle, or the tower of Hanoi solution * relevant to classical cognitive science because it is a finite physical mechanism that can create infinite variety |
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successor function |
* in arithmetic, all natural numbers can be represented by a primitive recursive function * an example of recursion >>> a finite physical mechanism that can create infinite variety * a recursive rule system in mathematics |
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sierpinksi triangle |
* infinite triangles within triangles * another example of a recursive rule system * again shows that a finite physical mechanism can create infinite variety |
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Tower of Hanoi |
* problem can be solved by recursion because the program calls on itself * another example of a recursive rule system * again shows that finite physical mechanism can create infinite variety |
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phrase markers |
* Chomsky used phrase markers to represent the structure of sentences * they make linear order of words, parts of speech, and constituent structure * it is a finite set of rewrite rules * it can generate an infinite variety of phrase markers, because the rules can be applied recursively * the repeated, recursive use of the rewrite rules of a context-free grammar can be used to infinitely elaborate a phrase marker by expanding its clauses |
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context-free grammar |
* context free grammar is a set of production rules that describe all possible strings in a given language * expressions generated from a context-free grammar can be complicated and cannot be accommodated by a finite state automaton * CF grammars are important in cognitive science because they are used to generate the phrase-markers |
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finite state automaton |
* an alternative to a Turing machine * a machine that interacts with a set of symbols written on a ticker tape * can only move in one direction and can only read (not write) symbols on the tape * the symbols that it encounters, in combination with the current physical state of the device, determine the new physical state of the device. * important for behaviour-based robotics |
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Turing machine |
* simple, powerful device for manipulating symbols according to a set of rules * 2 parts: an infinitely long ticker tape memory, and a machine head that can read and manipulate the symbols on the tape * behaviour of machine dictated by machine table that stores the possible actions of the machine head * current symbol, current machine state = selection of action from machine table * a question answering device * a particular machine table creates the UTM: can pretend to be any possible Turing machine * inspiration for the modern digital computer and foundation of classical cognitive science |
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universal Turing machine |
* particular form of Turing machine that is capable of mimicking the behaviour of any possible Turing machine * the power of the UTM comes from its ability to follow the program that describes any possible Turing machine, meaning that the universal machine can perform any possible computation * this power has fueled the information-processing hypothesis - that cognition is symbol manipulation - that is at the heart of classical cognitive science |
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informant learning |
* an approach to language learning that is a description of the language environment * learner is presented with both grammatical and ungrammatical examples of the language being learned, and is also informed about the grammaticality of each example. * Gold proved that complex grammars can only be identified in the limit via informant learning which led to Gold's paradox because it was later discovered that children learn complex languages in text environments |
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text learning |
* form of learning in which a language learner is only presented grammatical examples of a language (positive information) in contrast with informant learning * Gold showed that text learning is much less effective than informant learning * however, understanding text learning is crucial to cognitive science because evidence shows that human children learn their first language as text learners, not as informant learners (GOLD'S PARADOX) |
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Gold's paradox |
* Gold showed that text learning was not powerful enough to teach a system a complex grammar. * However, children learn complex natural languages via text learning * Important to cognitive science because it motivated new studies of human language learning, in an attempt to find a way around the paradox |
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poverty of the stimulus |
* claim that primary linguistic data do not contain enough information to uniquely specify the grammar used to produce them * responsible for formal proofs that text learning of a language is not possible if language is defined by a complex grammar |
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nativism |
* theory that most basic skills are hard-wired in the brain at birth * opposite of blank slate theory / tabula rasa * in linguistics, theory that the ability to learn grammar is hard-wired into the brain |
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universal grammar |
* Chomsky says the only way people can get away with the problem of text learning is that we are armed with genetic ability * this kind of nativist view is common in classical cognitive science * architecture of cognition is innate in regards to language |
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underdetermination |
* information available from the environment is not sufficient to support a unique interpretation or inference * for example, Gold proved that text learning of language was not enough to determine the grammar * important because it is a problem that needs to be solved. The text language problem (Gold's paradox) was "solved" by classical cognitive scientists stating that human language is innately available |
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* physical symbol system |
* broad class of systems that is capable of having and manipulating symbols, yet is also realizable within our physical universe * a computer is an example because it is a physical thing that manipulates symbols * in classical cognitive psychology, the brain is the physical symbol system. It contains symbols and rules to manipulate them. |
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Jacquard's loom |
* physical symbol system * cards held together by string to define a program for producing a fabric of a particular design * it was imagined that a program could be used to weave numbers, not thread. this idea led to the first computers |
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Newell and Simon's production system |
* program made of series of conditional statements that specify what action is to be taken under certain circumstances * environmental information is matched against all productions to determine next action * one of first attempts to model cognitive behaviour and form the basis of many existing models of cognition |
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ACT - adaptive control of thought |
* represents an evolution of the production system architecture * 2 major innovations: introduction of declarative memory to serve as a store of knowledge independent of productions, and introduction of learning mechanisms that permitted new productions to be added * still exemplifies the classical sandwich |
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classical sandwich |
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intentionality |
* "aboutness" * in classical cognitive science, a property of mental representations: cognitive agents have beliefs, knowledge, hopes, dreams, desires, etc... about things. * separates the psychological from the physical * any theory of mind must answer how intentionality is possible. |
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cognitive vocabulary? language of thought |
* classical cognitive science assumes that cognition is produced by a physical symbol system * this device carries out mental algorithms, in what Fodor called the "language of thought" * the language of thought specifies the functional architecture in terms of primitive symbols and operations that can be applied to them |
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structure/process distinction |
* structure = symbols processing the data * process = rules operating on the symbols * classical cognitive science makes a key distinction between the two * particular structures make some information more easily available, and particular operations are designed to process easily available information. * classical cognitive science must discover the structure/process pairings that are employed in different cognitive systems |
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Turing test |
* behavioural approach to determine whether or not a system is intelligent * a judge has conversations with a human and a robot and if the judge cannot tell the difference after a period of time, the machine is intelligent * some researchers say that it is strong and crucial to defining intelligence, while others say that it is too weak because many different systems can generate correct behaviours for incorrect reasons (ELIZA) |
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ELIZA |
* program that passed a version of the Turing test by carrying out impressive conversations * demonstration of how one could create an apparently intelligent interactive system with simple rules * weak equivalence: generates the correct output for the incorrect reasons * demonstrates weakness of the Turing test |
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weak equivalence AKA Turing equivalence |
* relationship between the outputs of two systems that are being compared * computing the same function (same external behaviour), but using different procedures to do so. * for example, human chess player VS computer * Turing test offers this kind of comparison. Although necessary for validating theories in cognitive science, it is not sufficient. Systems must compute these functions in the same way |
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strong equivalence |
* if two systems are strongly equivalent, they: - use the same program to compute this function * as far as "algorithmic" approaches to cognitive science are concerned, the aim of the discipline is to generate strongly equivalent theories of people |
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evidence for equivalence |
* functional analysis: collecting evidence to establish strong equivalence * error: does the model make the same kinds of errors as the subject? * relative complexity: are different problems of the same relative difficulty for the model and subject? * do model and subject go through the same intermediate information processing steps? * cognitive penetrability |
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cognitive penetrability |
* an approach to testing strong equivalence * does so by investigating whether a function of interest is primitive or not (part of the functional architecture or not) * penetrable = not part of the architecture impenetrable = part of functional architecture * used in imagery debate in 1980's cognitive science |
