Project Details
Description
This project brings together research into model-based AI diagnosis and planning with discrete optimisation, with the aim of benefiting both.
The AI planning and discrete-event diagnosis problem model, in which the solution is a sequence/schedule of state transitions, is substantially different from the traditional model in terms of decision variables and constraints that characterises optimisation methods such as constraint or mathematical programming. Nevertheless, planning and diagnosis are optimisation problems, in that the quality of solutions (plans or diagnoses) as well as the time spent finding them are primary concerns.
Thus, the aims of this project are to map concepts and ideas from optimisation into AI planning and diagnosis, demonstrating that these can be used to create new solution methods, and to extend the optimisation "tool kit" with the AI planning/diagnosis problem model and solution methods
Status | Finished |
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Effective start/end date | 1/01/15 → 30/06/16 |
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