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Answer Set Planning under Action Costs

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Logics in Artificial Intelligence (JELIA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2424))

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Abstract

We present \( \mathcal{K}^c \), which extends the declarative planning language \( \mathcal{K} \) by action costs and optimal plans that minimize overall action costs (cheapest plans). As shown, this novel language allows for expressing some nontrivial planning tasks in an elegant way. Furthermore, it flexibly allows for representing planning problems under other optimality criteria as well, such as computing “fastest” plans (with the least number of steps), and refinement combinations of cheap and fast plans. Our experience is encouraging and supports the claim that answer set planning may be a valuable approach to advanced planning systems in which intricate planning tasks can be naturally specified and effectively solved.

This work was supported by FWF (Austrian Science Funds) under the projects P14781 and Z29-INF

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Eiter, T., Faber, W., Leone, N., Pfeifer, G., Polleres, A. (2002). Answer Set Planning under Action Costs. In: Flesca, S., Greco, S., Ianni, G., Leone, N. (eds) Logics in Artificial Intelligence. JELIA 2002. Lecture Notes in Computer Science(), vol 2424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45757-7_16

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  • DOI: https://doi.org/10.1007/3-540-45757-7_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44190-8

  • Online ISBN: 978-3-540-45757-2

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