Determining linearity of optimal plans by operator schema analysis

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2 Citations (Scopus)

Abstract

Analysing the structures of solution plans generated by AI Planning engines is helpful in improving the generative planning process, as well as shedding light in the study of its theoretical foundations.We investigate a specific property of solution plans, that we called linearity, which refers to a situation where each action achieves an atom (or atoms) for a directly following action, or achieves goal atom(s). Similarly, linearity can be defined for parallel plans where each action in a set of actions executed at some time step, achieves either goal atom(s) or atom(s) for some action executed in the directly following time step. In this paper, we present a general and problem-independent theoretical framework focusing on the analysis of planning operator schema, namely relations of achiever, clobberer and independence, in order to determine whether solvable planning problems using a given operator schema have as solutions optimal (parallel) plans which are linear. The findings presented in this paper deepen current theoretical knowledge, provide helpful information to engineers of new planning domain models, and suggest new ways of improving the performance of state-of-theart (optimal) planning engines.

Original languageEnglish
Title of host publicationProceedings of the 10th Symposium on Abstraction, Reformulation, and Approximation, SARA 2013
Pages34-41
Number of pages8
Publication statusPublished - 2013
Event10th Symposium on Abstraction, Reformulation, and Approximation - Leavenworth, United States
Duration: 11 Jul 201312 Jul 2013
https://www.aaai.org/ocs/index.php/SARA/SARA13 (Link to Symposium Details )

Conference

Conference10th Symposium on Abstraction, Reformulation, and Approximation
Abbreviated titleSARA 2013
CountryUnited States
CityLeavenworth
Period11/07/1312/07/13
Internet address

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Cite this

Chrpa, L., Vallati, M., & McCluskey, T. L. (2013). Determining linearity of optimal plans by operator schema analysis. In Proceedings of the 10th Symposium on Abstraction, Reformulation, and Approximation, SARA 2013 (pp. 34-41)