Time-Critical Dynamic Decision Making
This work addresses the challenge of computational tractability in dynamic decision making for applications requiring real-time responses, representing an incremental improvement in existing methods.
The paper tackles the problem of dynamic decision modeling under time-critical conditions by proposing a time-critical dynamic influence diagram with two forms for modeling and inference, and a knowledge-based meta-reasoning approach to select abstracted models that balance quality and tractability.
Recent interests in dynamic decision modeling have led to the development of several representation and inference methods. These methods however, have limited application under time critical conditions where a trade-off between model quality and computational tractability is essential. This paper presents an approach to time-critical dynamic decision modeling. A knowledge representation and modeling method called the time-critical dynamic influence diagram is proposed. The formalism has two forms. The condensed form is used for modeling and model abstraction, while the deployed form which can be converted from the condensed form is used for inference purposes. The proposed approach has the ability to represent space-temporal abstraction within the model. A knowledge-based meta-reasoning approach is proposed for the purpose of selecting the best abstracted model that provide the optimal trade-off between model quality and model tractability. An outline of the knowledge-based model construction algorithm is also provided.