Using Planning for Query Decomposition in Bioinformatics

Domains like bioinformatics are complexdata integration domains because data from remote sources and specialized applications need to be combined to answer queries. An important characteristic of such a domain is that actions may be mutually exclusive or causally related. Moreover, there is (partially complete) domain specific knowledge about how queries should be answered since an average user is a sophisticated domain expert. Query plans in these domains should not only answer the query but also respect any user intent or domain guidance provided to improve the perceived quality of the result and query execution time. Previously, methods like rule inversion and view unfolding have been found to be more effective than AI planning in obtaining access sequences for sources without interactions, a case when sources are just repositories of data. We present a solution in SHQPlanner, a hierarchical temporal planner for query planning and execution monitoring in complex domains based on previous theoretical work on HTN planning with partial domain knowledge on one hand and temporal reasoning for query cost on the other. SHQPlanner is a sound, complete, and efficient domain-independent query planner that can incorporate partial query decomposition, source preferences, data and application interaction, and temporal constraints.

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