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<Paper uid="C65-1014">
  <Title>BABY G R</Title>
  <Section position="1" start_page="0" end_page="0" type="metho">
    <SectionTitle>
,C ..~
1965 International Conference on Computational Linguistics
SOME CO~ONENTS OF A PROGRm',\[ FOR DYNAMIC MODELLING
OF HISTORICAL CHANGE IN'LANGUAGE
</SectionTitle>
    <Paragraph position="0"/>
  </Section>
  <Section position="2" start_page="0" end_page="0" type="metho">
    <SectionTitle>
SOME COMPONENTS OF A PROGRAM FOR DYNg.MIC MODELLING
OF HISTORICAL CHANGE IN LANGUAGE
Sheldon Klein
ABSTRACT
</SectionTitle>
    <Paragraph position="0"> A system that is to serve as a vehicle for testing models of language change is being programmed in jOVIAL. Inherent in the design of the system is the requirement that each member of a speech community be represented by a generation grammar and a recognition grammar. The units of interaction in a simulation are conversations. Grammar rules may be borrowed or lost by individuals during the course of a simulation. The rules themselves need not be limited to those suggested by a particular theory of lanquaqe; also, they may refer to any or all levels of linguistic phenomena. Extralinquistic factors pertinent to language change may be incorporated in simulations.</Paragraph>
    <Paragraph position="1"> Klein I.</Paragraph>
  </Section>
  <Section position="3" start_page="0" end_page="0" type="metho">
    <SectionTitle>
1.0 The Simulation System
</SectionTitle>
    <Paragraph position="0"> A general simulation system which is to serve as a device for testing of hypotheses about language change through time is being program~ned in JOVIAL, an ALGOL language, and is partially operation1 a! on the Philco computer (4). The basic assumptions about the nature of language change inherent in the design of the Program include the notion of generation grammar, Bloomfield's concept of speech community (i), and Sapir's concept of genetic drift (5).</Paragraph>
    <Paragraph position="1"> Aside from these built in concepts, the program is designed as a vehicle for testing models of language change as a function of variables selected at the discretion of an experimenter. It is intended that the simulation system be sufficiently flexible to work with either transformational or stratificational models of language; to simulate the interaction of members of a speech community among themselves and with members of other communities; to model special relations among particular members, e.g. family groups and social classes; to simulate multilanguage acquisition; and to model the transmission of language from generation to generation.</Paragraph>
    <Paragraph position="2"> A basic assumption of the simulation system is that the interaction among members of a speech community is the prime  focal point of language change. Each member of a speech community or sample from a speech community is represented by boZh a generation grammar and a recognition grammar. Members of a community who are familiar with more than one language may be represented by additional gray,mars. The contents of the grammars may vary among individuals.</Paragraph>
    <Paragraph position="3"> Grammars of newborn children would be empty. An adult entering a new community as a speaker of an alien language might acquire an empty recognition and generation grammar to supplement the nonempty ones representing the languages he knows.</Paragraph>
    <Paragraph position="4"> The basic units of interaction are speech forms produced in response to other speech forms. ~ primary function of the system is to simulate conversations among members of a speech community.</Paragraph>
    <Paragraph position="5"> During the course of a conversation, one individual will generate a form and another will attempt to parse it. Should the parser's rules be inadequate for the task, he mayborrow the necessary rules from the generation grammar of the speaker, and perhaps use it when it is his turn to speak. Note that a bilingual speaker might attempt parsings with rules from all of his grammars.</Paragraph>
    <Paragraph position="6"> Many decisions within the simulation system are made with the use of random numbers and functions governing the transition from one state of events to another. Monte Carlo techniques will be used in conducting simulations. Basically, the term refers to the use of random elements to solve essentially deterministic problems which may be too complicated to solve by deterministic methods. Accordingly, to evaluate the predictions of such a system, it is essential to determine the effects of different choices of Klein 3.</Paragraph>
    <Paragraph position="7"> random numbers numbers upon the results, if the model is deterministic, the results of repeated trials relying on different inputs of random numbers should be similar.</Paragraph>
  </Section>
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