5 CONSTRAINT SATISFACTION PROBLEMS
5CONSTRAINTSATISFACTIONPROBLEMSInwhich weseehowtreatingstatesasmore thanjustlittleblack boxesleadsto theinventionofa range ofpowerfulnew search methodsanda deeperunderstandingofproblemstructure and4 exploredtheideathatproblemscanbesolvedby searchinginaspaceofstates. Thesestatescanbeevaluatedbydomain-specif icheuristicsandtestedtoseewhetherthey ,however,eachstateis is representedbyanarbi-BLACKBOXtrarydatastr ucturethatcanbeaccessedonlybytheproblem- specificroutines thesuccessorfunction,heuristicfunction, , whosestatesandgoaltestconformtoa standard,structured,andverysimplereprese ntation( ).Searchal-REPRESENTATIONgorithmscanbede finedthattake advantageofthestructureofstatesandusegen eral-purposeratherthanproblem-specifiche uristicsto enablethesolutionoflargeproblems( ).Perhapsmostimportantly, thestandardrepresentationofthegoaltestre vealsthestruc-tureoftheproblemitself( ).Thisleadstomethodsforproblemdecomposit ionandtoanunderstandingoftheintimateconn ectionbetweenthestructureofa ,aconstraintsatisfactionproblem(orCSP)is definedbya setofvari-CONSTRAINTSATISFACTIONPROBLEMa bles,X1; X2; : : : ; Xn, anda setofconstraints,C1; C2; : : : ; Cm.
}Goal test: the current assignment is complete.}Path cost: a constant cost (e.g., 1) for every step. Every solution must be a complete assignment and therefore appears at depth n if there are n variables. Furthermore, the search tree extends only to depth n. For these reasons, depth-first search algorithms are popular for CSPs. (See Section 5.2.)
Download 5 CONSTRAINT SATISFACTION PROBLEMS
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: