Anytime algorithm: Difference between revisions

Revision as of 01:07, 30 January 2023

Revision as of 09:04, 11 February 2023

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== Goals ==

The goal of anytime algorithms are to give [[Hybrid intelligent system|intelligent systems]] the ability to make results of better quality in return for turn-around time.<ref name="Zilberstein">{{harvnb|Zilberstein|1996}} </ref> They are also supposed to be flexible in time and resources.<ref name="Grass">{{cite journal |first=J. |last=Grass |title=Reasoning about computational resource allocation. XRDS: Crossroads |journal=The ACM Magazine for Students |volume=3 |issue=1 |pages=16–20 |date=1996 |doi=10.1145/332148.332154 |s2cid=45448244 |url=https://dl.acm.org/doi/pdf/10.1145/332148.332154|doi-access=free }}</ref> They are important because [[artificial intelligence]] or AI algorithms can take a long time to complete results. This algorithm is designed to complete in a shorter amount of time.<ref name="Grass"/> Also, these are intended to have a better understanding that the system is dependent and restricted to its agents and how they work cooperatively.<ref name="Grass"/> An example is the [[Newton–Raphson]] iteration applied to finding the square root of a number.<ref name="FOLDOC">[http://foldoc.org/anytime+algorithm anytime algorithm from Free Online Dictionary of Computing (FOLDOC)]</ref> Another example that uses anytime algorithms is trajectory problems when you're aiming for a target; the object is moving through space while waiting for the algorithm to finish and even an approximate answer can significantly improve its accuracy if given early.<ref name="Grass"/>

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* {{cite conference |arxiv=1301.7384 |last1=Horsch |first1=M.C. |last2=Poole |first2=D. |title=An anytime algorithm for decision making under uncertainty |book-title=Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence |date=1998 |isbn=978-1-55860-555-8 |pages=246–255 |url=http://www.cs.ubc.ca/spider/poole/papers/randaccref.pdf}}

* {{cite techreport |first=E.J. |last=Horvitz |title=Reasoning about inference tradeoffs in a world of bounded resources |publisher=Medical Computer Science Group, Section on Medical Informatics, Stanford University |id=KSL-86-55 |date=March 1986 |url=}}

* {{cite journal |last1=Wallace |first1=R. |last2=Freuder |first2=E. |title=Anytime Algorithms for Constraint Satisfaction and SAT Problems |journal= ACM SIGART Bulletin |volume=7 |issue=2 |pages=7–10 |date=1995 |doi=10.1145/242587.242589 |s2cid=8250394 |url=https://dl.acm.org/doi/abs/10.1145/242587.242589|doi-access=free }}

* {{cite thesis |first=S. |last=Zilberstein |title=Operational Rationality through Compilation of Anytime Algorithms |publisher=Computer Science Division, University of California at Berkeley |type=PhD |date=1993 |url=https://dl.acm.org/doi/abs/10.5555/193131 |id=UMX GAX94-08166}}

*{{cite journal |first=Shlomo |last=Zilberstein |title=Using Anytime Algorithms in Intelligent Systems |journal=AI Magazine |volume=17 |issue=3 |pages=73–83 |date=1996 |doi= |url=http://rbr.cs.umass.edu/shlomo/papers/Zaimag96.pdf}}