Collaborative Context-based Reasoning
2007
- 275Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage275
- Downloads261
- Abstract Views14
Thesis / Dissertation 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.
Bibliographic Details
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