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1、1IntroductionSungwookYoon,PostdoctoralResearchAssociateLecturematerialandHomeworkisavailableoncoursewebpageThelecturesareintendedtogiveoverviewofplanningresearchinAISmatteringofrecentprogressesContentsClassicalplanningDefinitionsBasicalgorithmicparadig
2、msMarkovDecisionProcesses(MDPs)Basicdefinitionsandsolutiontechniques2Homework1DueApril25AvailablefromCourseWeb-Page3ClassicalSTRIPSPlanningClassicalplanningassumptionsSTRIPSactionlanguageWhatisaplanningproblem?complexityofplanningPlanningasSearchState-
3、spacesearchSungwookYoon**BasedinpartonslidesbyAlanFernandDanielWeld.4PerceptsActionsWorldperfectvs. noisyfully observablevs. partially observableinstantaneousvs. durativedeterministicvs. stochasticAIPlanning????solesource ofchangevs. othersources5Perce
4、ptsActions????Worldperfectfully observableinstantaneousdeterministicClassicalPlanningAssumptionssolesource ofchange6RepresentingStatesholding(A)clear(B)on(B,C)onTable(C)State1handEmptyclear(A)on(A,B)on(B,C)onTable(C)State2CABCABWorldstatesarerepresente
5、dassetsoffacts.Wewillalsorefertofactsaspropositions.ClosedWorldAssumption(CWA):Factnotlistedinastateareassumedtobefalse.UnderCWA weareassumingtheagenthasfullobservability.7RepresentingGoalsGoalsarealsorepresentedassetsoffacts.Forexample{on(A,B)}isagoal
6、intheblocksworld.Agoalstateisanystatethatcontainsallthegoalfacts.handEmptyclear(A)on(A,B)on(B,C)onTable(C)State1CABholding(A)clear(B)on(B,C)onTable(C)State2CABState1isagoalstateforthegoal{on(A,B)}. State2isnotagoalstate.8RepresentingActioninSTRIPSholdi
7、ng(A)clear(B)on(B,C)onTable(C)State1handEmptyclear(A)on(A,B)on(B,C)onTable(C)State2Stack(A,B)CABCABASTRIPSactiondefinitionspecifies: 1)asetPREofpreconditionsfacts 2)asetADDofaddeffectfacts 3)asetDELofdeleteeffectfactsStack(x,y):PRE:{holding(x),clear(y)
8、}ADD:{on(x,y),handEmpty}DEL:{holding(x),clear(y)}Stack(A,B):PRE:{holding(A),clear(B)}ADD:{on(A,B),handEmpty}DEL:{holding(A),clear(B)}x←Ax←B9SemanticsofSTRIPSActionsholding(A)clear(B)on(B,C)onTable(C)ShandEmptyclear(A)on(A,B)on(B,C)onTab
