Local Search for Planning and Scheduling: ECAI 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers (Lecture Notes in Computer Science, 2148) - Softcover
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.
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Local Search for Planning and Scheduling : Ecai 2000 Workshop, Berlin, Germany, August 21, 2000 : Revised Papers
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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, 2148)
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Local Search for Planning and Scheduling
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Taschenbuch. Condition: 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 GMDFIRST AngeloOddi IP-CNR Mar aC. Ri Univ. T ec. Fed. SantaMar 184 pp. Englisch. Seller Inventory # 9783540428985
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Local Search for Planning and Scheduling: Ecai 2000 Workshop, Berlin, Germany, August 21, 2000. Revised Papers (Paperback or Softback)
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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, 2148)
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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)
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