Knowledge-based formulation of dynamic decision models
Conference Proceeding Article
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.
Artificial Intelligence and Robotics
Data Management and Analytics
PRICAI'98: Topics in Artificial Intelligence
City or Country
Wang, Chenggang Wang and Tze-Yun LEONG.
Knowledge-based formulation of dynamic decision models. (1998). PRICAI'98: Topics in Artificial Intelligence. 1531, 506-517. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3058
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