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<Paper uid="W91-0111">
  <Title>COMMON HEURISTICS FOR PARSING, GENERATION, AND WHATEVER...</Title>
  <Section position="3" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> One lesson to learn from the repeated failure to design large AI systems in general is that the information flow in the cognitive systems is too complex and diverse to stipulate in the design of these AI systems. To capture this diversity of information flow. therefore. At systeins must be designed at a more abstract level where direction of information flow is not explicit,.</Paragraph>
    <Paragraph position="1"> This is where constrai~t paradigm comes in. Since constraints do not stipulate the direction of information flow or processing Order, constraint-based systems could be tailored to halve tractable complexity, unlike procedural systems, which stipulate information flow and thus quickly become too colnplex for human designers to extend or maintain.</Paragraph>
    <Paragraph position="2"> Naturally, the key issue in the constraint-based approach is how to control information flow. A very general control schema independent of any specific domain or task is vitally Ile('essal'y for the success of this approach. null The present paper introduces a system of constraint in a \[o,-m of logic progi'am, and a set of very general heuristics to control symbolic operation on the constraints. The sS'mboli( I operations herr are r('gar(h'd as Iransforming logic programs. &amp;quot;lhcv are quite permissivr operations as a whole, allowing very diverse information processing involving top-down, bottom-up and other directions of informal ion flow. The heuristics control this computation so that only relevant information should be exploited and the resuhing representation should be compact. Parsing and generation of sentences are shown to be efficiently done under these heuristics, and a standard parsing algorithm and the semantic head-driven generation \[8\] naturally emerge thereof.</Paragraph>
    <Paragraph position="3"> The rest of the paper is organized as follows. Section 2 describes the syntax of our system of constraint. Section 3 defines the symbolic computation on these constraints, and proposes a set of general heuristics to control computation. Section 4 and Section 5 show how sentence parsing and generation are executed efficiently by those heuristics. Finally, Section 6 concludes the paper.</Paragraph>
    <Paragraph position="4"> 8.1.</Paragraph>
  </Section>
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