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<Paper uid="C65-1014">
  <Title>BABY G R</Title>
  <Section position="4" start_page="0" end_page="5" type="concl">
    <SectionTitle>
2.0 Components
</SectionTitle>
    <Paragraph position="0"> The basic components of the the simulation system consist of a table containing the grammar rules and parameters associated with each individual in the simulation; a generation and parsing device that makes use of the grammars of interacting individuals; a table of functional relationships containing the rules of interaction pertinent to a particular simulation model; and, finally, a monitor program thai determines the flow of the simulation and the passage of time, and that periodically takes a census to inform the experimenter of the changes occuring at various stages of the simulation.</Paragraph>
    <Paragraph position="1"> The first version of the simulation system is being constructed around the author's automatic essay paraphrasing system (2) which produces essaylike paraphrases of an input consisting of a restricted English text and an outline of the desired output essay. The syntactic style of the output is controlled by manipulation of parameters pertaininq to the frequency of usage of specific generation grammar rules (3).</Paragraph>
    <Paragraph position="2"> The table of functional relationships thai contains the definition of a particular model of language change might include rules expressing such features as: i. Members of the same social group are more likely to speak to each other than.to members of other groups.</Paragraph>
    <Paragraph position="3"> 2. Each time an individual interacts with a particular member of the community the probability of future interactions with thai Klein 4.</Paragraph>
    <Paragraph position="4"> member increases.</Paragraph>
    <Paragraph position="5"> More complex functions pertaining to particular socio-cultural conditions might also be used.</Paragraph>
    <Paragraph position="6"> Other functions might control the deletion of infrequently used grammar rules, or the shift of a grammar rule from a recognition qrammar to a qeneration qrammar.</Paragraph>
    <Paragraph position="7"> The monitoring system is designed to work with a mixed assortment of functional relationships pertaining to very different phenomena. At a given decision point the monitor scans the table of functions sequentially until it finds an applicable item.</Paragraph>
    <Section position="1" start_page="0" end_page="5" type="sub_section">
      <SectionTitle>
3.0 A Hand Simulation
</SectionTitle>
      <Paragraph position="0"> The nature and function of the basic components can be illustrated by a hand simulation of the flow of an extremely simple language model.</Paragraph>
      <Paragraph position="1"> Let the population contain six members: JOHN, ~4ARY, HELEN, PETER, HE~.~N and BABY. Let each have a separate generation and recognition grammar. Let each be assigned a status in the range of .Ol to .99, and let the letters A,B,C,D,E,F represent the grammar rules existinq in the community. (See table i.) The content of the rules is deliberately left unspecified. The rules may refer to semantics, syntax, morphology and/or phonology. Each rule is associated with a weighted frequency. A rule with a frequency weight less than a specified threshold value (.i in this simulation) can exist only in a recognition grammar. A rule with a frequency weight greater than or equal to the threshold must exist both in an individual's generation and recognition grammars. A rule existing in both grammars has the same frequency weight in each. A rule whose weight drops  below a minimum value (.i in this simulation) is deleted from all qrammars.</Paragraph>
      <Paragraph position="2"> Table 1 contains a record of the various states of the speech community at time Ti,j, where i refers to a major cycle--a single individual's interaction with a variety of speakers, and where j refers to a minor cycle--the interval of an interaction with a single speaker. At each increment in the value i, the monitor randomly selects a member as speaker for a major cycle.&amp;quot; The monitor then scans the population Sequentially to determine which members are to be auditors of the speaker. The determination follows the appropriate function contained in table 2. Each time an auditor is selected, the minor cycle time j is incremented by i. When the monitor has scanned the entire community, the speaker's turn is over and a new one is selected to ~ ~o~ the next major Cycle.</Paragraph>
      <Paragraph position="3"> At the beginning of each major cycle the j or minor cycle value is set to zero. The data in column T0, 0 of table 1 are startlng data supplied by the author. The data existing at Ti, j is used in comDutinq the state of events during Ti,j~ 1 . Blank entries in table 1 indicate that the state of events is unchanged from the previous interval.</Paragraph>
      <Paragraph position="4"> Table 2 contains the list of active rules refered to by the monitor during the course of the simulation. All computed values qreater than or equal to 1 are rounded to .99; values computed at less than or equal to 0 are rounded to .01~ in all cases, computed values are rounded to the second decimal place.</Paragraph>
      <Paragraph position="5">  The simulation begins at time T0, 1 rather than at time T0, 0 for initialization purposes: T0,1 The monitor selects }&amp;~RY as speaker for the 0 cycle, and examines the list of potential auditors. The first candidate is JOHN. Accordinq to function 1 of table 2 the probability of }4ARY speakinq 9o /OHN is .i divided by the absolute value of the status difference of the pair: .i =-.99 (rounded) /.7 VS-/&amp;quot; Y~RY will speak to JOHN because the random n~mber qenerator of the monitor fails to yield a value greater than .99. Assume that ~v~Y generates the form: G(A, 2D) which is to be interpreted as indicatinq tha~ in the generation, JO~N is able to parse the rule A was used once, rule D twice, u.form with his o~ ~ecoqnition~rules, and their frequency weights are a!tered accordinq to functions 2 and 3 in table 2. Rule A is computed as:  ~ $OHN's recoqnition rules B and C were not used in the parsinq; after function 3 of table 2each of their weiqhts is decremented by.02. According to function 6 of table 2, }~RY's new status becomes:  The monitor searches for Y~,RY's next auditor. ,,~,~degv~ is skipped as a,candidate. HELEN.is next. The probability of IVLARY speaking * io HELEN after function ! of table 2 is: ' ' .! : ! 7.'7&amp;quot;2&amp;quot;- . 4:/-Assume HELEN is rejected as an auditor because monitor's random number generator produces a value greater than this. Assume that the next auditor candidate, PETER, is also rejected. The monitor then selects HERf~IAN as the next candidate. Now assume that HER\]v~N is selected as auditor after appropriate computations. Let f,\[ARY's generated utterance be: @(A, 2B) ~.~,,,~ musfi borrow rule A froml YblRY's generation grammar to complete the parsing* Rule A enters HER~'~%N,s recognition grammar, by function 2 of table 2, with a value: 0- (0 - *33) : .07 &amp;quot;&amp;quot; 5'&amp;quot;' Since this value is less than .i, it does not enter HERMAN's generation grammar. The new value of B is computed as:</Paragraph>
      <Paragraph position="7"> The rules not used in parsing are decremented by 02 HE~IIA~ s recognition rule D, accordingly, drops below the minimum retention value of *0~,and is deleted from his recognition grammar.</Paragraph>
      <Paragraph position="8">  The preceding hand S'imulation should be sufficient to illustrate the operation of the simulation system. Anticipated computer simulations will involve 50 to 100 individuals, each associated with several&lt;hundred grammar rules, iUnique ~ parsings can be obtained by using 6xistinq frequency weights to determine preferential applicability of 'rules. The functions contained in table 2 can be qreatly extended in number and content. One miqht wish to add special rules for interaction between :parent ,'and Child, spouses, and among members of the same age'group, etc., plus a mechanism for determining the birth and death of various members. The status factor might be divided into weights refering to social status, aqe, geographical proximity and the like.</Paragraph>
      <Paragraph position="9"> The ideal test of the validity of a simulation is prediction.</Paragraph>
      <Paragraph position="10"> Hopefully, one miqht predict an attested state of a language from a model of an attested earlier stage. A major problem in such testing may be i i~.xlreme sensitivity of a model to the choice of parameter values and constants. For example, the constants in the functions of table 2 seem to have the effect of making BABY learn too quickly. One might use a higher rate of decay for unused Klein 15.</Paragraph>
      <Paragraph position="11"> rules to decrease the learning rate. The need for trial and error manipulation of values will increase with the complexity of a model. Accordingly, one might start with simple models, increasing the complexity by stages.</Paragraph>
      <Paragraph position="12"> The author's immediate research goal is to produce a stability simulation involving about 50 members,each associated with a simple phrase structure gra~nar of ~ ~nqmish, over a time span of 3 or 4 qenerations--a simulation in which the language at the start of the simulation is reasonably similar to the language existing at the conclusion.</Paragraph>
    </Section>
  </Section>
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