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Local Search for Planning and Scheduling: ECAI 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) - Couverture souple

 
9783540428985: Local Search for Planning and Scheduling: ECAI 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)

Synopsis

This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Local Search for Planning and Scheduling, held at a satellite workshop of ECAI 2000 in Berlin, Germany in August 2000. The nine revised full papers presented together with an invited survey on meta-heuristics have gone through two rounds of reviewing and improvement. The papers are organized in topical sections on combinatorial optimization, planning with resources, and related approaches.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

  • ÉditeurSpringer
  • Date d'édition2001
  • ISBN 10 3540428984
  • ISBN 13 9783540428985
  • ReliureBroché
  • Langueanglais
  • Nombre de pages184
  • ÉditeurNareyek Alexander
  • Coordonnées du fabricantnon disponible

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Nareyek, Alexander
Edité par Springer Berlin Heidelberg, 2001
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Invited Paper.- Meta-heuristics: The State of the Art.- Combinatorial Optimization.- Solving the Sports League Scheduling Problem with Tabu Search.- Lagrange Multipliers for Local Search on Planning Graphs.- Planning with Resources.- Beyond the Plan-Length . N° de réf. du vendeur 4890131

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Alexander Nareyek
Edité par Springer Berlin Heidelberg, 2001
ISBN 10 : 3540428984 ISBN 13 : 9783540428985
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Withtheincreasingdeploymentofplanningandschedulingsystems,developer s oftenhavetodealwithverylargesearchspaces,real-timeperformancedemands, anddynamicenvironments. Completere nementmethodsdonotscalewell,- kinglocalsearchmethodstheonlypracticalalternative. Adynamicenvironment alsopromotestheapplicationoflocalsearch,thesearchheuristicsnotnormally beinga ectedbymodi cationsofthesearchspace. Furthermore,localsearchis wellsuitedforanytimerequirementsbecausetheoptimizationgoalisimproved iteratively. Suchadvantagesareo setbytheincompletenessofmostlocalsearch methods,whichmakesitimpossibletoprovetheinconsistencyoroptimalityof thesolutionsgenerated. Popularlocalsearchapproachesincludeevolutionary- gorithms,simulatedannealing,tabusearch,min-con icts,GSAT,andWalksat. The rstarticleinthisbook aninvitedcontributionbyStefanVoß givesan overviewofthesemethods. ThebookisbasedonthecontributionstotheWorkshoponLocalSearchfor Planning&Scheduling,heldonAugust21,2000atthe14thEuropeanCon- renceonArti cialIntelligence(ECAI2000)inBerlin,Germany. Theworkshop broughttogetherresearchersfromtheplanningandschedulingcommunitiesto explorethesetopicswithrespecttolocalsearchprocedures. Aftertheworkshop, asecondreviewprocessresultedinthecontributionstothepresentvolume. Voß soverviewisfollowedbytwoarticles,byHamiezandHaoandGerevini andSerina,onspeci c classical combinatorialsearchproblems. Thearticleby HamiezandHaoaddressestheproblemofsports-leaguescheduling,presenting results achieved by a tabu search method based on a neighborhood of value swaps. GereviniandSerina sarticleaddressesthetopicthatdominatestherest ofthebook:actionplanning. Itbuildsontheirpreviousworkonlocalsearch onplanninggraphs,presentinganewsearchguidanceheuristicwithdynamic parametertuning. Thenextsetofarticlesdealwithplanningsystemsthatareabletoinc- porateresourcereasoning. The rstarticle,ofwhichIamtheauthor,makesit clearwhyconventionalplanningsystemscannotproperlyhandleplanningwith resourcesandgivesanoverviewoftheconstraint-basedExcaliburagent spl- ningsystem,whichdoesnothavetheserestrictions. Thenextthreearticlesare aboutNASAJPL sASPEN/CASPERsystem. The rstone byChien,Knight, andRabideau focusesonthereplanningcapabilitiesoflocalsearchmethods, presentingtwoempiricalstudiesinwhichacontinuousplanningprocessclearly outperformsarestartstrategy. Thenextarticle,byEngelhardtandChien,shows howlearningcanbeusedtospeedupthesearchforaplan. Thegoalisto nda setofsearchheuristicsthatguidethesearchaswellaspossible. Thelastarticle inthisblock byKnight,Rabideau,andChien proposesanddemonstrates, a technique for aggregating single search moves so that distant states can be reachedmoreeasily. VI Preface Thelastthreearticlesinthisbookaddresstopicsthatarenotdirectlyrelated tolocalsearch,butthedescribedmethodsmakeverylocaldecisionsduringthe search. RefanidisandVlahavasdescribeextensionstotheGRTplanner,e. g. ,a hill-climbingstrategyforactionselection. Theextensionsresultinmuchbetter performancethanwiththeoriginalGRTplanner. Thesecondarticle byO- india, Sebastia, and Marzal presents a planning algorithm that successively re nes a start graph by di erent phases, e. g. , a phase to guarantee comp- teness. Inthelastarticle,HiraishiandMizoguchipresentasearchmethodfor constructingaroutemap. Constraintswithrespecttomemoryandtimecanbe incorporatedintothesearchprocess. Iwishtoexpressmygratitudetothemembersoftheprogramcommittee, whoactedasreviewersfortheworkshopandthisvolume. Iwouldalsoliketo thank all those who helped to make this workshop a success including, of course,theparticipantsandtheauthorsofpapersinthisvolume. June2001 AlexanderNareyek WorkshopChair ProgramCommittee EmileH. L. Aarts PhilipsResearch Jos eLuisAmbite Univ. ofSouthernCalifornia BlaiBonet UniversityofCalifornia RonenI. Brafman Ben-GurionUniversity SteveChien NASAJPL AndrewDavenport IBMT. J. Watson AlfonsoGerevini Universit`adiBrescia HolgerH. Hoos Univ. ofBritishColumbia AlexanderNareyek GMDFIRST AngeloO. N° de réf. du vendeur 9783540428985

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Withtheincreasingdeploymentofplanningandschedulingsystems,developers oftenhavetodealwithverylargesearchspaces,real-timeperformancedemands, anddynamicenvironments. Completere nementmethodsdonotscalewell,- kinglocalsearchmethodstheonlypracticalalternative. Adynamicenvironment alsopromotestheapplicationoflocalsearch,thesearchheuristicsnotnormally beinga ectedbymodi cationsofthesearchspace. Furthermore,localsearchis wellsuitedforanytimerequirementsbecausetheoptimizationgoalisimproved iteratively. Suchadvantagesareo setbytheincompletenessofmostlocalsearch methods,whichmakesitimpossibletoprovetheinconsistencyoroptimalityof thesolutionsgenerated. Popularlocalsearchapproachesincludeevolutionary- gorithms,simulatedannealing,tabusearch,min-con icts,GSAT,andWalksat. The rstarticleinthisbook aninvitedcontributionbyStefanVoß givesan overviewofthesemethods. ThebookisbasedonthecontributionstotheWorkshoponLocalSearchfor Planning&Scheduling,heldonAugust21,2000atthe14thEuropeanCon- renceonArti cialIntelligence(ECAI2000)inBerlin,Germany. Theworkshop broughttogetherresearchersfromtheplanningandschedulingcommunitiesto explorethesetopicswithrespecttolocalsearchprocedures. Aftertheworkshop, asecondreviewprocessresultedinthecontributionstothepresentvolume . Voß soverviewisfollowedbytwoarticles,byHamiezandHaoandGerevini andSerina,onspeci c classical combinatorialsearchproblems. Thearticleby HamiezandHaoaddressestheproblemofsports-leaguescheduling,presenting results achieved by a tabu search method based on a neighborhood of value swaps. GereviniandSerina sarticleaddressesthetopicthatdominatestherest ofthebook:actionplanning. Itbuildsontheirpreviousworkonlocalsearch onplanninggraphs,presentinganewsearchguidanceheuristicwithdynam ic parametertuning. Thenextsetofarticlesdealwithplanningsystemsthatareabletoinc- porateresourcereasoning. The rstarticle,ofwhichIamtheauthor,makesit clearwhyconventionalplanningsystemscannotproperlyhandleplanningwith resourcesandgivesanoverviewoftheconstraint-basedExcaliburagent spl- ningsystem,whichdoesnothavetheserestrictions. Thenextthreearticlesare aboutNASAJPL sASPEN/CASPERsystem. The rstone byChien,Knight, andRabideau focusesonthereplanningcapabilitiesoflocalsearchmethods, presentingtwoempiricalstudiesinwhichacontinuousplanningprocessclearly outperformsarestartstrategy. Thenextarticle,byEngelhardtandChien,shows howlearningcanbeusedtospeedupthesearchforaplan. Thegoalisto nda setofsearchheuristicsthatguidethesearchaswellaspossible. Thelastarticle inthisblock byKnight,Rabideau,andChien proposesanddemonstrates, a technique for aggregating single search moves so that distant states can be reachedmoreeasily. VI Preface Thelastthreearticlesinthisbookaddresstopicsthatarenotdirectlyrelated tolocalsearch,butthedescribedmethodsmakeverylocaldecisionsduringthe search. RefanidisandVlahavasdescribeextensionstotheGRTplanner,e. g. ,a hill-climbingstrategyforactionselection. Theextensionsresultinmuchbetter performancethanwiththeoriginalGRTplanner. Thesecondarticle byO- india, Sebastia, and Marzal presents a planning algorithm that successively re nes a start graph by di erent phases, e. g. , a phase to guarantee comp- teness. Inthelastarticle,HiraishiandMizoguchipresentasearchmethodfor constructingaroutemap. Constraintswithrespecttomemoryandtimecanbe incorporatedintothesearchprocess. Iwishtoexpressmygratitudetothemembersoftheprogramcommittee, whoactedasreviewersfortheworkshopandthisvolume. Iwouldalsoliketo thank all those who helped to make this workshop a success including, of course,theparticipantsandtheauthorsofpapersinthisvolume. June2001 AlexanderNareyek WorkshopChair ProgramCommittee EmileH. L. Aarts PhilipsResearch Jos eLuisAmbite Univ. ofSouthernCalifornia BlaiBonet UniversityofCalifornia RonenI. Brafman Ben-GurionUniversity SteveChien NASAJPL AndrewDavenport IBMT. J. Watson AlfonsoGerevini Universit`adiBrescia HolgerH. Hoos Univ. ofBritishColumbia AlexanderNareyek. N° de réf. du vendeur 9783540428985

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Taschenbuch. Etat : Neu. Neuware -Thenextsetofarticlesdealwithplanningsystemsthatareabletoinc- porateresourcereasoning. The rstarticle,ofwhichIamtheauthor,makesit clearwhyconventionalplanningsystemscannotproperlyhandleplanningwith resourcesandgivesanoverviewoftheconstraint-basedExcaliburagent¿spl- ningsystem,whichdoesnothavetheserestrictions. Thenextthreearticlesare aboutNASAJPL¿sASPEN/CASPERsystem. The rstone¿byChien,Knight, andRabideaüfocusesonthereplanningcapabilitiesoflocalsearchmethods, presentingtwoempiricalstudiesinwhichacontinuousplanningprocessclearl y outperformsarestartstrategy. Thenextarticle,byEngelhardtandChien,shows howlearningcanbeusedtospeedupthesearchforaplan. Thegoalisto nda setofsearchheuristicsthatguidethesearchaswellaspossible. Thelastarticle inthisblock¿byKnight,Rabideau,andChien¿proposesanddemonstrates, a technique for aggregating single search moves so that distant states can be reachedmoreeasily. VI Preface Thelastthreearticlesinthisbookaddresstopicsthatarenotdirectlyrelated tolocalsearch,butthedescribedmethodsmakeverylocaldecisionsduringthe search. RefanidisandVlahavasdescribeextensionstotheGRTplanner,e. g. ,a hill-climbingstrategyforactionselection. Theextensionsresultinmuchbetter performancethanwiththeoriginalGRTplanner. Thesecondarticle¿byO- india, Sebastia, and Marzal ¿ presents a planning algorithm that successively re nes a start graph by di erent phases, e. g. , a phase to guarantee comp- teness. Inthelastarticle,HiraishiandMizoguchipresentasearchmethodfor constructingaroutemap. Constraintswithrespecttomemoryandtimecanbe incorporatedintothesearchprocess. Iwishtoexpressmygratitudetothemembersoftheprogramcommittee, whoactedasreviewersfortheworkshopandthisvolume. Iwouldalsoliketo thank all those who helped to make this workshop a success ¿ including, of course,theparticipantsandtheauthorsofpapersinthisvolume. June2001 AlexanderNareyek WorkshopChair ProgramCommittee EmileH. L. Aarts PhilipsResearch Jos¿eLuisAmbite Univ. ofSouthernCalifornia BlaiBonet UniversityofSpringer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 184 pp. Englisch. N° de réf. du vendeur 9783540428985

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