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<Paper uid="C96-1008">
  <Title>Communication in large distributed AI Systems for Natural Language Processing</Title>
  <Section position="7" start_page="39" end_page="39" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> We have presented the concepts and implementation of a communication system designed for use in large AI systems which nowadays are typically built to operate in a distributed manner within local networks of workstations. We argued that the adaptation of sound theoretical concepts which for example can be found in Hoare (1978) lead to solutions that have considerably more power that ad-hoc communication devices implemented as the need to communicate arises. 'rim channel model was slightly modified and realized on top of l?VM, a de facto standard for communication in distributed systems. The system structure reflects a set of components that communicate bilaterally without the involvement of a central mechanism or data structure that participates in every comrnunication event. Instead, once the identity of the communication partners is established, cornmunication between them is strictly local.</Paragraph>
    <Paragraph position="1"> We introduced a central name server in order to store the components acting in an application and to be able to service requests for the creation of channels and such. Channels come in two flavors what on the one hand guarantees succesful comrnunication between any two partners and on the other hand leaves room for tailoring properties of message channels to certain preferences. Furthermore, split channels allow for the easy configuration of a system with respect to interchangeable parts of the system and attached visualization.</Paragraph>
    <Paragraph position="2"> We showed that the communication system realized using this methods is advantegeous in several situations and system contexts, ranging fi'om strictly sequential systems over intermediary forms to highly interactive systems.</Paragraph>
  </Section>
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