Addressing the Qualification Problem in FLUX

The Qualification Problem arises for planning agents in real-world environments, where unexpected circumstances may at any time prevent the successful performance of an action. We present a logic programming method to cope with the Qualification Problem in the action programming language Flux, which builds on the Fluent Calculus as a solution to the fundamental Frame Problem. Our system allows to plan under the default assumption that actions succeed as they normally do, and to reason about these assumptions in order to recover from unexpected action failures.

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