Self-adjusting real-time search: a summary of results

Shashi Shekhar, Babak Hamidzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Real-time search algorithms need to address the deadlines imposed by applications like process control and robot navigation. Possible deadline violations should be predicted ahead of time to allow remedial actions to prevent the undesirable consequences of missing deadlines. The algorithms should also demonstrate progressively optimizing behavior. That is, they should improve the quality of the solutions as time constraints are relaxed. To successfully address these issues, a real-time search algorithm must address the central problem of choosing the proper values for its parameters, which control the time allocated to planning. We proposed a new approach to determine the parameter values of a real-time search algorithm, in order to enable the algorithm to meet deadlines, exhibit progressively optimizing behavior, and to predict deadline violation prior to the deadline. The paper provides a theoretical and experimental characterization of the proposed algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Tools with Artificial Intelligence
Editors Anon
PublisherPubl by IEEE
Pages224-231
Number of pages8
ISBN (Print)0818642009
StatePublished - Dec 1 1993
EventProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93 - Boston, MA, USA
Duration: Nov 8 1993Nov 11 1993

Publication series

NameProceedings of the International Conference on Tools with Artificial Intelligence
ISSN (Print)1063-6730

Other

OtherProceedings of the 5th International Conference on Tools with Artificial Intelligence TAI '93
CityBoston, MA, USA
Period11/8/9311/11/93

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