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Situated Natural Language Interactio...
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Williams, Thomas E.
Situated Natural Language Interaction in Uncertain and Open Worlds.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
Situated Natural Language Interaction in Uncertain and Open Worlds./
作者:
Williams, Thomas E.
面頁冊數:
1 online resource (391 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
標題:
Computer science. -
電子資源:
click for full text (PQDT)
ISBN:
9781369833492
Situated Natural Language Interaction in Uncertain and Open Worlds.
Williams, Thomas E.
Situated Natural Language Interaction in Uncertain and Open Worlds.
- 1 online resource (391 pages)
Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Thesis (Ph.D.)--Tufts University, 2017.
Includes bibliographical references
As intelligent agents become integrated into our society, it becomes increasingly important for them to be capable of engaging in natural, human-like human-agent interactions. A key aspect of such interactions is the ability to engage in pragmatically appropriate natural language dialogues. That is, intelligent agents must be able to understand and generate natural language expressions in a way that is sensitive to their current environmental context, social context, and dialogue state.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9781369833492Subjects--Topical Terms:
573171
Computer science.
Index Terms--Genre/Form:
554714
Electronic books.
Situated Natural Language Interaction in Uncertain and Open Worlds.
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Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
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Adviser: Matthias J. Scheutz.
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Thesis (Ph.D.)--Tufts University, 2017.
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As intelligent agents become integrated into our society, it becomes increasingly important for them to be capable of engaging in natural, human-like human-agent interactions. A key aspect of such interactions is the ability to engage in pragmatically appropriate natural language dialogues. That is, intelligent agents must be able to understand and generate natural language expressions in a way that is sensitive to their current environmental context, social context, and dialogue state.
520
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This problem is especially difficult in the uncertain and open worlds common to typical human-robot interaction scenarios, in which a robot cannot be expected to have perfect or complete knowledge of its environment. What is more, many of the approaches that have been developed to facilitate human-robot dialogues are tailored to specific knowledge representation schemes or particular domains of information that prevent them from being generally applicable across robot architectures or across application domains.
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To address these concerns, I have developed a set of algorithms for understanding and generating natural language in uncertain and open worlds, and a set of general frameworks and architectural mechanisms that allow these algorithms to be agnostic to representational format and application domain whenever possible. The algorithms and architectural mechanisms presented in this dissertation represent an interdisciplinary approach to artificial intelligence, in which cognitive science is drawn upon to provide theoretical frameworks (e.g., Speech Act Theory, the Givenness Hierarchy), and cognitive models (e.g. the Incremental Algorithm), and in which computer science is drawn upon to provide computational frameworks (e.g., Multi-Agent Systems, Integrated Robot Architectures) and techniques (Dempster-Shafer Theory, logical inference, search).
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In this dissertation, I demonstrate how these algorithms and architectural mechanisms can be integrated into a single natural language processing pipeline within an integrated robot architecture. What is more, I show how this integrated system extends the state of the art in domains such as natural language enabled wheelchairs when implemented on robot hardware.
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click for full text (PQDT)
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