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COLLABORATIVE CONTEXT-BASED REASONING

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Date Issued:
2007
Abstract/Description:
This dissertation explores modeling collaborative behavior, based on Joint Intentions Theory (JIT), in Context-Based Reasoning (CxBR). Context-Based Reasoning is one of several contextual reasoning paradigms. And, Joint Intentions Theory is the definitive semantic framework for collaborative behaviors. In order to formalize collaborative behaviors in CxBR based on JIT, CxBR is first described in terms of the more popular Belief, Desire, and Intention (BDI) model. Once this description is established JIT is used as a basis for the formalism for collaborative behavior in CxBR. The hypothesis of this dissertation is that this formalism allows for effective collaborative behaviors in CxBR. Additionally, it is also hypothesized that CxBR agents inferring intention from explicitly communicating Contexts allows for more efficient modeling of collaborative behaviors than inferring intention from situational awareness. Four prototypes are built and evaluated to test the hypothesis and the evaluations are favorable. Effective collaboration is demonstrated through cognitive task analysis and through metrics based on JIT definitions. Efficiency is shown through software metric evaluations for volume and complexity of code.
Title: COLLABORATIVE CONTEXT-BASED REASONING.
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Name(s): Barrett, Gilbert, Author
Gonzalez, Avelino, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2007
Publisher: University of Central Florida
Language(s): English
Abstract/Description: This dissertation explores modeling collaborative behavior, based on Joint Intentions Theory (JIT), in Context-Based Reasoning (CxBR). Context-Based Reasoning is one of several contextual reasoning paradigms. And, Joint Intentions Theory is the definitive semantic framework for collaborative behaviors. In order to formalize collaborative behaviors in CxBR based on JIT, CxBR is first described in terms of the more popular Belief, Desire, and Intention (BDI) model. Once this description is established JIT is used as a basis for the formalism for collaborative behavior in CxBR. The hypothesis of this dissertation is that this formalism allows for effective collaborative behaviors in CxBR. Additionally, it is also hypothesized that CxBR agents inferring intention from explicitly communicating Contexts allows for more efficient modeling of collaborative behaviors than inferring intention from situational awareness. Four prototypes are built and evaluated to test the hypothesis and the evaluations are favorable. Effective collaboration is demonstrated through cognitive task analysis and through metrics based on JIT definitions. Efficiency is shown through software metric evaluations for volume and complexity of code.
Identifier: CFE0001667 (IID), ucf:47198 (fedora)
Note(s): 2007-05-01
Ph.D.
Engineering and Computer Science, School of Electrical Engineering and Computer Science
Doctorate
This record was generated from author submitted information.
Subject(s): teamwork
collaborative
behavior
context based reasoning
joint intention theory
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0001667
Restrictions on Access: public
Host Institution: UCF

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