Reactive Query Policies: A Formalism for Planning with Volatile External Information

To generate plans for collecting data for data mining, an important problem is information volatility during planning: the information needed by the planning system may change or expire during the planning process, as changes occur in the data being collected. In such situations, the planning system faces two challenges: how to generate plans despite these changes, and how to guarantee that a plan returned by the planner will remain valid for some period of time after the planning ends. The focus of our work is to address both of the above challenges. In particular, we provide: 1) A formalism for reactive query policies, a class of strategies for deciding when to reissue queries for information that has changed during the planning process. This class includes all query management strategies that have yet been developed. 2) A new reactive query policy called the presumptive strategy. In our experiments, the presumptive strategy ran exponentially faster than the lazy strategy, the best previously known query management strategy. In the hardest set of problems we tested, the presumptive strategy took 4.7% as much time and generated 6.9% as many queries as the lazy strategy