Numeric Kernel for Reasoning about Plans Involving Numeric Fluents

The paper proposes the notion of numeric kernel as a means for reasoning about plans involving numeric state variables, i.e. numeric fluents. A numeric kernel identifies the sufficient and necessary conditions that allow to directly - without any search and any propagation - assess whether a plan is valid in a specific world state. The notion generalizes the propositional kernels defined for the STRIPS language, to support domains involving numeric information as well. A regression method to build such kernels is reported, and its correctness is theoretically proved. To evaluate the numeric kernels contribution, we report two possible repair strategies that can be employed as a direct application of the numeric kernel properties. Results show the promise of the approach both from the computational point of view and in terms of plan quality.