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On Improving Plan Quality via Local Enhancements

Publication at Faculty of Mathematics and Physics |
2012

Abstract

There exist planning algorithms that can quickly find suboptimal plans even for large problems and planning algorithms finding optimal plans but only for smaller problems. We attempt to integrate both approaches.

We present an anytime technique for improving plan quality (decreasing the plan makespan) via substituting parts of the plan by better sub-plans. The technique guarantees optimality though it is primarily intended to quickly improve plan quality.

We experimentally compare various approaches to local improvements.