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020 _a9783540245810
_9978-3-540-24581-0
024 7 _a10.1007/b94701
_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
245 1 0 _aAI 2003: Advances in Artificial Intelligence
_h[electronic resource] :
_b16th Australian Conference on AI, Perth, Australia, December 3-5, 2003, Proceedings /
_cedited by Tamas D. Gedeon, Lance C.C. Fung.
250 _a1st ed. 2003.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2003.
300 _aXXXII, 1078 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 ;
_v2903
505 0 _aKeynote Papers -- Ontology -- Problem Solving -- Knowledge Discovery and Data Mining I -- Knowledge Discovery and Data Milling II -- Expert Systems -- Neural Networks Applications -- Belief Revisioii and Theorem Proving -- Reasoning and Logic -- Machine Learning I -- AI Applications -- Neural Networks -- Intelligent Agents -- Computer Vision -- AI & Medical Applications -- Machine Learning II -- Machilie Learning and Language -- Artificial Intelligence I -- AI \& Business -- Soft Computing -- Language Understanding -- Theory -- Artificial Intelligence II.
520 _aConsider the problem of a robot (algorithm, learning mechanism) moving along the real line attempting to locate a particular point ? . To assist the me- anism, we assume that it can communicate with an Environment (“Oracle”) which guides it with information regarding the direction in which it should go. If the Environment is deterministic the problem is the “Deterministic Point - cation Problem” which has been studied rather thoroughly [1]. In its pioneering version [1] the problem was presented in the setting that the Environment could charge the robot a cost which was proportional to the distance it was from the point sought for. The question of having multiple communicating robots locate a point on the line has also been studied [1, 2]. In the stochastic version of this problem, we consider the scenario when the learning mechanism attempts to locate a point in an interval with stochastic (i. e. , possibly erroneous) instead of deterministic responses from the environment. Thus when it should really be moving to the “right” it may be advised to move to the “left” and vice versa. Apart from the problem being of importance in its own right, the stoch- tic pointlocationproblemalsohas potentialapplications insolvingoptimization problems. Inmanyoptimizationsolutions–forexampleinimageprocessing,p- tern recognition and neural computing [5, 9, 11, 12, 14, 16, 19], the algorithm worksits wayfromits currentsolutionto the optimalsolutionbasedoninfor- tion that it currentlyhas. A crucialquestionis oneof determining the parameter whichtheoptimizationalgorithmshoulduse.
650 0 _aArtificial intelligence.
650 0 _aComputer science.
650 0 _aMachine theory.
650 0 _aDatabase management.
650 0 _aInformation storage and retrieval systems.
650 0 _aApplication software.
650 1 4 _aArtificial Intelligence.
650 2 4 _aTheory of Computation.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aDatabase Management.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputer and Information Systems Applications.
700 1 _aGedeon, Tamas D.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFung, Lance C.C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540206460
776 0 8 _iPrinted edition:
_z9783662181102
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v2903
856 4 0 _uhttps://doi.org/10.1007/b94701
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
912 _aZDB-2-BAE
942 _cSPRINGER
999 _c188030
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