Abstract
The paper addresses the problem of supervising the execution of a plan with durative actions in a just partially known world, where discrepancies between the expected conditions and the ones actually found may arise. The paper advocates a control architecture which exploits additional knowledge to prevent (when possible) action failures by changing the execution modality of actions while these are still in progress. Preliminary experimental results, obtained in a simulated space exploration scenario, are reported.
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Micalizio, R., Scala, E., Torasso, P. (2011). Intelligent Supervision for Robust Plan Execution. In: Pirrone, R., Sorbello, F. (eds) AI*IA 2011: Artificial Intelligence Around Man and Beyond. AI*IA 2011. Lecture Notes in Computer Science(), vol 6934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23954-0_16
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DOI: https://doi.org/10.1007/978-3-642-23954-0_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23953-3
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