Knowledge-based formulation of dynamic decision models
We present a new methodology to automate decision making over time and uncertainty. We adopt a knowledge-based model construction approach to support automated and interactive formulation of dynamic decision models, i.e., models that explicitly consider the effects of time. Our work integrates and e...
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sg-smu-ink.sis_research-40582016-02-05T06:30:05Z Knowledge-based formulation of dynamic decision models Wang, Chenggang Wang Tze-Yun LEONG, We present a new methodology to automate decision making over time and uncertainty. We adopt a knowledge-based model construction approach to support automated and interactive formulation of dynamic decision models, i.e., models that explicitly consider the effects of time. Our work integrates and extends different features of the existing frameworks. We incorporate a hybrid knowledge representation scheme that integrates categorical knowledge, probabilistic knowledge, and deterministic knowledge. We provide a set of knowledge-based modification operations for automatic and interactive generation, abstraction, and refinement of the model components. We have built a knowledge base in a real-world domain and shown that it can support automated construction of a reasonable dynamic decision model. The results indicate the practical promise of the proposed design. 1998-11-27T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/3058 info:doi/10.1007/BFb0095296 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics |
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We present a new methodology to automate decision making over time and uncertainty. We adopt a knowledge-based model construction approach to support automated and interactive formulation of dynamic decision models, i.e., models that explicitly consider the effects of time. Our work integrates and extends different features of the existing frameworks. We incorporate a hybrid knowledge representation scheme that integrates categorical knowledge, probabilistic knowledge, and deterministic knowledge. We provide a set of knowledge-based modification operations for automatic and interactive generation, abstraction, and refinement of the model components. We have built a knowledge base in a real-world domain and shown that it can support automated construction of a reasonable dynamic decision model. The results indicate the practical promise of the proposed design. |
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Wang, Chenggang Wang Tze-Yun LEONG, |
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Wang, Chenggang Wang Tze-Yun LEONG, |
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Wang, Chenggang Wang |
title |
Knowledge-based formulation of dynamic decision models |
title_short |
Knowledge-based formulation of dynamic decision models |
title_full |
Knowledge-based formulation of dynamic decision models |
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Knowledge-based formulation of dynamic decision models |
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Knowledge-based formulation of dynamic decision models |
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knowledge-based formulation of dynamic decision models |
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Institutional Knowledge at Singapore Management University |
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1998 |
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