Abstract
The encoded negative literals in a conformant planning task will result in increasing state spaces. Getting a compact representation of state spaces is one of the most important issues in conformant planning. In this paper, a translation algorithm for negative literals is proposed to reduce the state spaces in a conformant planning task. The relationship between encoded literals is analyzed in detail. Based on the one-of relaxation technique in domain language, the algorithm is used to express the uncertain initial states and action effects in conformant planning. It converts formula one-of into a set of mutually exclusive literals with the relationship of mutual. The experiment study shows the efficiency of the proposed algorithm in pruning the state space in conformant planning tasks.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
