Abstract
The marriage of model checking and planning faces two seemingly diverging alternatives: the need for a planning language expressive enough to capture the complexity of real-life applications, as opposed to a language simple, yet robust enough to be amenable to exhaustive verification and validation techniques. In an attempt to reconcile these differences, we have designed an abstract plan description language, ANMLite, inspired from the Action Notation Modeling Language (ANML). We present the basic concepts of the ANMLite language as well as an automatic translator from ANMLite to the model checker SAL (Symbolic Analysis Laboratory). We discuss various aspects of specifying a plan in terms of constraints and explore the implications of choosing a robust logic behind the specification of constraints, rather than simply propose a new planning language. Additionally, we provide an initial assessment of the efficiency of model checking to search for solutions of planning problems. To this end, we design a basic test benchmark and study the scalability of the generated SAL models in terms of plan complexity.
Research funding was provided by the National Aeronautics and Space Administration under the cooperative agreement NCC-1-02043.
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Siminiceanu, R.I., Butler, R.W., Muñoz, C.A. (2009). Experimental Evaluation of a Planning Language Suitable for Formal Verification. In: Peled, D.A., Wooldridge, M.J. (eds) Model Checking and Artificial Intelligence. MoChArt 2008. Lecture Notes in Computer Science(), vol 5348. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00431-5_9
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DOI: https://doi.org/10.1007/978-3-642-00431-5_9
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