Anytime algorithm - Revision history

OAbot: Open access bot: url-access updated in citation with #oabot.

2025-05-24T08:44:03Z

Open access bot: url-access updated in citation with #oabot.

← Previous revision		Revision as of 08:44, 24 May 2025
Line 38:		Line 38:
	{{refbegin}}		{{refbegin}}
	*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}		*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592\|url-access=subscription }}
	* {{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 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 tech report \|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 tech report \|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=}}

MrOllie: /* Examples */ rm single entry list

2025-03-14T15:24:49Z

Examples: rm single entry list

← Previous revision		Revision as of 15:24, 14 March 2025
Line 31:		Line 31:
	*Growth rate: Amount of increase with each step. Does it change constantly, such as in a [[bubble sort]] or does it change unpredictably?		*Growth rate: Amount of increase with each step. Does it change constantly, such as in a [[bubble sort]] or does it change unpredictably?
	*End condition: The amount of runtime needed<ref name="Teije"/>		*End condition: The amount of runtime needed<ref name="Teije"/>

	== Examples ==
	There are many famous anytime algorithms in the literature. We list here some of them.

	* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[partially observable Markov decision process]]es.<ref>{{Cite journal \|last1=Pineau \|first1=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th International Joint Conference on Artificial Intelligence \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 }}</ref>

	==References==		==References==

BunnysBot: Fix CW Errors with GenFixes (T1)

2025-02-01T10:11:46Z

Fix CW Errors with GenFixes (T1)

← Previous revision		Revision as of 10:11, 1 February 2025
Line 8:		Line 8:

	== Goals ==		== 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 \|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"/>		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 \|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"/>

	What makes anytime algorithms unique is their ability to return many possible outcomes for any given input.<ref name="Zilberstein"/> An anytime algorithm uses many well defined quality measures to monitor progress in [[problem solving]] and [[distributed computing]] resources.<ref name="Zilberstein"/> It keeps searching for the best possible answer with the amount of time that it is given.<ref name="umich">{{cite web\|title=Anytime algorithms\|url=http://ai.eecs.umich.edu/cogarch2/index.html\|website=Cognitive architectures\|publisher=University of Michigan Artificial Intelligence Laboratory\|archiveurl=https://web.archive.org/web/20131213011435/http://ai.eecs.umich.edu/cogarch2/cap/anytime.plan\|archivedate=13 December 2013}}</ref> It may not run until completion and may improve the answer if it is allowed to run longer.<ref name="elook">{{cite web\|title=Anytime algorithm - Computing Reference\|url=http://www.elook.org/computing/anytime-algorithm.htm\|website=eLook.org\|archiveurl=https://web.archive.org/web/20131212094200/http://www.elook.org/computing/anytime-algorithm.htm\|archivedate=12 December 2013}}</ref>		What makes anytime algorithms unique is their ability to return many possible outcomes for any given input.<ref name="Zilberstein"/> An anytime algorithm uses many well defined quality measures to monitor progress in [[problem solving]] and [[distributed computing]] resources.<ref name="Zilberstein"/> It keeps searching for the best possible answer with the amount of time that it is given.<ref name="umich">{{cite web\|title=Anytime algorithms\|url=http://ai.eecs.umich.edu/cogarch2/index.html\|website=Cognitive architectures\|publisher=University of Michigan Artificial Intelligence Laboratory\|archiveurl=https://web.archive.org/web/20131213011435/http://ai.eecs.umich.edu/cogarch2/cap/anytime.plan\|archivedate=13 December 2013}}</ref> It may not run until completion and may improve the answer if it is allowed to run longer.<ref name="elook">{{cite web\|title=Anytime algorithm - Computing Reference\|url=http://www.elook.org/computing/anytime-algorithm.htm\|website=eLook.org\|archiveurl=https://web.archive.org/web/20131212094200/http://www.elook.org/computing/anytime-algorithm.htm\|archivedate=12 December 2013}}</ref>
Line 35:		Line 35:
	There are many famous anytime algorithms in the literature. We list here some of them.		There are many famous anytime algorithms in the literature. We list here some of them.

	* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[~~Partially~~ observable Markov decision process~~\|partially observable Markov decision processes~~]]<ref>{{Cite journal \|last1=Pineau \|first1=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th International Joint Conference on Artificial Intelligence \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 }}</ref>.		* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[partially observable Markov decision process]]es.<ref>{{Cite journal \|last1=Pineau \|first1=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th International Joint Conference on Artificial Intelligence \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 }}</ref>

	==References==		==References==

Citation bot: Altered journal. Add: authors 1-1. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Jay8g | Category:CS1 errors: DOI | #UCB_Category 2/4

2025-01-27T21:35:03Z

Altered journal. Add: authors 1-1. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Jay8g | Category:CS1 errors: DOI | #UCB_Category 2/4

← Previous revision		Revision as of 21:35, 27 January 2025
Line 35:		Line 35:
	There are many famous anytime algorithms in the literature. We list here some of them.		There are many famous anytime algorithms in the literature. We list here some of them.

	* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[Partially observable Markov decision process\|partially observable Markov decision processes]]<ref>{{Cite journal \|~~last~~=Pineau \|~~first~~=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th ~~international~~ ~~joint~~ ~~conference~~ on Artificial ~~intelligence~~ \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 ~~\|doi=10.5555/1630659.1630806~~}}</ref>.		* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[Partially observable Markov decision process\|partially observable Markov decision processes]]<ref>{{Cite journal \|last1=Pineau \|first1=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th International Joint Conference on Artificial Intelligence \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 }}</ref>.

	==References==		==References==

Fschwarzentruber: starting a list of "famous" anytime algorithms

2025-01-27T10:26:57Z

starting a list of "famous" anytime algorithms

← Previous revision		Revision as of 10:26, 27 January 2025
Line 31:		Line 31:
	*Growth rate: Amount of increase with each step. Does it change constantly, such as in a [[bubble sort]] or does it change unpredictably?		*Growth rate: Amount of increase with each step. Does it change constantly, such as in a [[bubble sort]] or does it change unpredictably?
	*End condition: The amount of runtime needed<ref name="Teije"/>		*End condition: The amount of runtime needed<ref name="Teije"/>

			== Examples ==
			There are many famous anytime algorithms in the literature. We list here some of them.

			* PBVI (point-based value iteration) is an anytime algorithm for [[Automated planning and scheduling\|automated planning]] in [[Partially observable Markov decision process\|partially observable Markov decision processes]]<ref>{{Cite journal \|last=Pineau \|first=Joelle \|last2=Gordon \|first2=Geoff \|last3=Thrun \|first3=Sebastian \|date=2003-08-09 \|title=Point-based value iteration: an anytime algorithm for POMDPs \|url=https://dl.acm.org/doi/10.5555/1630659.1630806 \|journal=Proceedings of the 18th international joint conference on Artificial intelligence \|series=IJCAI'03 \|location=San Francisco, CA, USA \|publisher=Morgan Kaufmann Publishers Inc. \|pages=1025–1030 \|doi=10.5555/1630659.1630806}}</ref>.

	==References==		==References==

AnnaBSP at 14:24, 18 November 2024

2024-11-18T14:24:10Z

← Previous revision		Revision as of 14:24, 18 November 2024
Line 47:		Line 47:

	{{DEFAULTSORT:Anytime Algorithm}}		{{DEFAULTSORT:Anytime Algorithm}}
	[[Category:Artificial intelligence]]		[[Category:Artificial intelligence engineering]]
	[[Category:Search algorithms]]		[[Category:Search algorithms]]

Headbomb: ce

2024-08-12T11:24:18Z

← Previous revision		Revision as of 11:24, 12 August 2024
Line 38:		Line 38:
	{{refbegin}}		{{refbegin}}
	*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}		*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}
	* {{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 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 tech report \|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 tech report \|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=}}

Tc14Hd: /* Goals */ Removed empty line

2024-07-15T22:59:48Z

Goals: Removed empty line

← Previous revision		Revision as of 22:59, 15 July 2024
Line 9:		Line 9:
	== Goals ==		== 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 \|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"/>		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 \|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"/>


	What makes anytime algorithms unique is their ability to return many possible outcomes for any given input.<ref name="Zilberstein"/> An anytime algorithm uses many well defined quality measures to monitor progress in [[problem solving]] and [[distributed computing]] resources.<ref name="Zilberstein"/> It keeps searching for the best possible answer with the amount of time that it is given.<ref name="umich">{{cite web\|title=Anytime algorithms\|url=http://ai.eecs.umich.edu/cogarch2/index.html\|website=Cognitive architectures\|publisher=University of Michigan Artificial Intelligence Laboratory\|archiveurl=https://web.archive.org/web/20131213011435/http://ai.eecs.umich.edu/cogarch2/cap/anytime.plan\|archivedate=13 December 2013}}</ref> It may not run until completion and may improve the answer if it is allowed to run longer.<ref name="elook">{{cite web\|title=Anytime algorithm - Computing Reference\|url=http://www.elook.org/computing/anytime-algorithm.htm\|website=eLook.org\|archiveurl=https://web.archive.org/web/20131212094200/http://www.elook.org/computing/anytime-algorithm.htm\|archivedate=12 December 2013}}</ref>		What makes anytime algorithms unique is their ability to return many possible outcomes for any given input.<ref name="Zilberstein"/> An anytime algorithm uses many well defined quality measures to monitor progress in [[problem solving]] and [[distributed computing]] resources.<ref name="Zilberstein"/> It keeps searching for the best possible answer with the amount of time that it is given.<ref name="umich">{{cite web\|title=Anytime algorithms\|url=http://ai.eecs.umich.edu/cogarch2/index.html\|website=Cognitive architectures\|publisher=University of Michigan Artificial Intelligence Laboratory\|archiveurl=https://web.archive.org/web/20131213011435/http://ai.eecs.umich.edu/cogarch2/cap/anytime.plan\|archivedate=13 December 2013}}</ref> It may not run until completion and may improve the answer if it is allowed to run longer.<ref name="elook">{{cite web\|title=Anytime algorithm - Computing Reference\|url=http://www.elook.org/computing/anytime-algorithm.htm\|website=eLook.org\|archiveurl=https://web.archive.org/web/20131212094200/http://www.elook.org/computing/anytime-algorithm.htm\|archivedate=12 December 2013}}</ref>

Citation bot: Misc citation tidying. | Use this bot. Report bugs. | #UCB_CommandLine

2023-07-24T22:19:50Z

Misc citation tidying. | Use this bot. Report bugs. | #UCB_CommandLine

← Previous revision		Revision as of 22:19, 24 July 2023
Line 41:		Line 41:
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}
	* {{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 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 tech report \|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 \|doi-access=free }}		* {{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 \|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 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}}

Citation bot: Removed proxy/dead URL that duplicated identifier. | Use this bot. Report bugs. | Suggested by Corvus florensis | #UCB_webform 3237/3500

2023-02-11T09:04:51Z

Removed proxy/dead URL that duplicated identifier. | Use this bot. Report bugs. | Suggested by Corvus florensis | #UCB_webform 3237/3500

← Previous revision		Revision as of 09:04, 11 February 2023
Line 8:		Line 8:

	== Goals ==		== 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"/>		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 \|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"/>


Line 42:		Line 42:
	* {{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 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 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 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 \|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 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}}		*{{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}}

← Previous revision		Revision as of 08:44, 24 May 2025
Line 38:		Line 38:
	{{refbegin}}		{{refbegin}}
	*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}		*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592\|url-access=subscription }}
	* {{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 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 tech report \|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 tech report \|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=}}

← Previous revision		Revision as of 11:24, 12 August 2024
Line 38:		Line 38:
	{{refbegin}}		{{refbegin}}
	*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}		*{{cite conference \|last1=Boddy \|first1=M. \|last2=Dean \|first2=T. \|title=Solving time-dependent planning problems \|book-title=Proceedings of the 11th international joint conference on Artificial intelligence \|volume=2 \|date=1989 \|isbn= \|pages=979–984 \|url=https://dl.acm.org/doi/abs/10.5555/1623891.1623912 \|id=Brown University CS-89-03}}
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=ACM SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}
	* {{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 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 tech report \|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 tech report \|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=}}

← Previous revision		Revision as of 22:19, 24 July 2023
Line 41:		Line 41:
	* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}		* {{cite journal \|last1=Grass \|first1=J. \|last2=Zilberstein \|first2=S. \|title=Anytime Algorithm Development Tools \|journal=SIGART Bulletin \|volume=7 \|issue=2 Special Issue on Anytime Algorithms and Deliberation Scheduling \|pages= 20–27\|date=1996 \|doi=10.1145/242587.242592 \|s2cid=7670055 \|url=https://dl.acm.org/doi/abs/10.1145/242587.242592}}
	* {{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 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 tech report \|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 \|doi-access=free }}		* {{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 \|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 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}}

← Previous revision		Revision as of 09:04, 11 February 2023
Line 8:		Line 8:

	== Goals ==		== 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"/>		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 \|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"/>


Line 42:		Line 42:
	* {{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 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 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 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 \|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 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}}		*{{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}}