000 03170nam a22005415i 4500
001 978-3-540-39607-9
003 DE-He213
005 20240423132548.0
007 cr nn 008mamaa
008 121227s2003 gw | s |||| 0|eng d
020 _a9783540396079
_9978-3-540-39607-9
024 7 _a10.1007/b93903
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aHoffmann, Jörg.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aUtilizing Problem Structure in Planning
_h[electronic resource] :
_bA Local Search Approach /
_cby Jörg Hoffmann.
250 _a1st ed. 2003.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2003.
300 _aXVIII, 254 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v2854
505 0 _aPlanning: Motivation, Definitions, Methodology -- 1: Introduction -- 2: Planning -- A Local Search Approach -- 3: Base Architecture -- 4: Dead Ends -- 5: Goal Orderings -- 6: The AIPS-2000 Competition -- Local Search Topology -- 7: Gathering Insights -- 8: Verifying the h?+? Hypotheses -- 9: Supporting the hFF Hypotheses -- 10: Discussion -- Appendix A: Formalized Benchmark Domains -- Appendix B: Automated Instance Generation.
520 _aPlanning is a crucial skill for any autonomous agent, be it a physically embedded agent, such as a robot, or a purely simulated software agent. For this reason, planning, as a central research area of artificial intelligence from its beginnings, has gained even more attention and importance recently. After giving a general introduction to AI planning, the book describes and carefully evaluates the algorithmic techniques used in fast-forward planning systems (FF), demonstrating their excellent performance in many wellknown benchmark domains. In advance, an original and detailed investigation identifies the main patterns of structure which cause the performance of FF, categorizing planning domains in a taxonomy of different classes with respect to their aptitude for being solved by heuristic approaches, such as FF. As shown, the majority of the planning benchmark domains lie in classes which are easy to solve.
650 0 _aArtificial intelligence.
650 0 _aAlgorithms.
650 1 4 _aArtificial Intelligence.
650 2 4 _aAlgorithms.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540202592
776 0 8 _iPrinted edition:
_z9783662182208
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v2854
856 4 0 _uhttps://doi.org/10.1007/b93903
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
912 _aZDB-2-BAE
942 _cSPRINGER
999 _c189150
_d189150