Abstract
This thesis is concerned with solving planning problems in deterministic and non-deterministic domains through explicit model checking techniques. The contribution is twofold: on one side we developed the V-UPMurphi tool, which applies a disk-based planning approach for efficient storage during the plan synthesis. On the other side we developed and formally analysed an algorithm to solve cost-optimal strong planning problems in non-deterministic contexts. Finally, we applied the developed algorithms and tools to several application domains, many of which are inspired by real world scenarios.
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