2017/02/07 by Sara Bernardini, Fabio Fagnani, Bernardini, Sara +4
Computer Science · #Software Engineering Research #AI-based Problem Solving and Planning #Advanced Software Engineering Methodologies
paper · pdf · doi:10.48550/arxiv.1702.01886
We present a technique for automatically extracting mutual exclusion\ninvariants from temporal planning instances. It first identifies a set of\ninvariant templates by inspecting the lifted representation of the domain and\nthen checks these templates against properties that assure invariance. Our\ntechnique builds on other approaches to invariant synthesis presented in the\nliterature, but departs from their limited focus on instantaneous actions by\naddressing temporal domains. To deal with time, we formulate invariance\nconditions that account for the entire structure of the actions and the\npossible concurrent interactions between them. As a result, we construct a\nsignificantly more comprehensive technique than previous methods, which is able\nto find not only invariants for temporal domains, but also a broader set of\ninvariants for non-temporal domains. The experimental results reported in this\npaper provide evidence that identifying a broader set of invariants results in\nthe generation of fewer multi-valued state variables with larger domains. We\nshow that, in turn, this reduction in the number of variables reflects\npositively on the performance of a number of temporal planners that use a\nvariable/value representation by significantly reducing their running time.\n