人工智能的课件CH8-FOL.ppt
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- 人工智能 课件 CH8 FOL
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1、智能计算研究中心X. First order logic (FOL) Autumn 2012Instructor: Wang XiaolongHarbin Institute of Technology, Shenzhen Graduate SchoolIntelligent Computation Research Center(HITSGS ICRC)2Outline Why FOL? Syntax and semantics of FOL Using FOL Wumpus world in FOL Knowledge engineering in FOL3Pros and cons of
2、 propositional logicJ Propositional logic is declarativeJ Propositional logic allows partial/disjunctive/negated information (unlike most data structures and databases)J Propositional logic is compositional: meaning of B1,1 P1,2 is derived from meaning of B1,1 and of P1,2J Meaning in propositional l
3、ogic is context-independent (unlike natural language, where meaning depends on context) Propositional logic has very limited expressive power (unlike natural language) E.g., cannot say pits cause breezes in adjacent squares“ except by writing one sentence for each square4First-order logic Whereas pr
4、opositional logic assumes the world contains facts First-order logic (like natural language) assumes a car contains Objects: people, houses, numbers, colors, baseball games, wars, Relations: red, round, prime, brother of, bigger than, part of, comes between, Functions: father of, best friend, one mo
5、re than, plus, 5Examples:“One plus two equals three”Objects:Relations:Properties:Functions:“Squares neighboring the Wumpus are smelly”Objects:Relations:Properties:Functions:6Examples:“One plus two equals three”Objects:one, two, three, one plus twoRelations:equalsProperties:-Functions:plus (“one plus
6、 two” is the name of the object obtained by applying function plus to one and two;three is another name for this object)“Squares neighboring the Wumpus are smelly”Objects:Wumpus, squareRelations:neighboringProperties:smellyFunctions:-7Semanticsthere is a correspondence between functions, which retur
7、n values predicates, which are true or falseFunction: father_of(Mary) = BillPredicate: father_of(Mary, Bill)8Syntax of FOL: Basic elements ConstantsKingJohn, 2, HIT,. PredicatesBrother, ,. FunctionsSqrt, LeftLegOf,. Variablesx, y, a, b,. Connectives, , , , Equality= Quantifiers , 9Atomic sentencesAt
8、omic sentence =predicate (term1,.,termn) or term1 = term2Term =function (term1,.,termn) or constant or variable E.g., Brother(KingJohn,RichardTheLionheart) (Length(LeftLegOf(Richard), Length(LeftLegOf(KingJohn)10Complex sentences Complex sentences are made from atomic sentences using connectivesS, S
9、1 S2, S1 S2, S1 S2, S1 S2,E.g. Sibling(KingJohn,Richard) Sibling(Richard,KingJohn) (1,2) (1,2) (1,2) (1,2) 11Truth in first-order logicSentences are true with respect to a model and an interpretationModel contains objects (domain elements) and relations among themInterpretation specifies referents f
10、orconstant symbols objectspredicate symbols relationsfunction symbols functional relationsAn atomic sentence predicate(term1,.,termn) is trueiff the objects referred to by term1,.,termnare in the relation referred to by predicate12Models for FOL: Example13Universal quantification Everyone at HIT is
11、smart:x At(x,HIT) Smart(x) x P is true in a model m iff P is true with x being each possible object in the model Roughly speaking, equivalent to the conjunction of instantiations of PAt(KingJohn, HIT) Smart(KingJohn) At(Richard, HIT) Smart(Richard) At(HIT, HIT) Smart(HIT) .14A common mistake to avoi
12、d Typically, is the main connective with Common mistake: using as the main connective with :x At(x, HIT) Smart(x)means “Everyone is at HIT and everyone is smart”15Existential quantification Someone at HIT is smart:x At(x, HIT) Smart(x) x P is true in a model m iff P is true with x being some possibl
13、e object in the modelRoughly speaking, equivalent to the disjunction of instantiations of PAt(KingJohn, HIT) Smart(KingJohn) At(Richard, HIT) Smart(Richard) At(HIT, HIT) Smart(HIT) .16Another common mistake to avoid Typically, is the main connective with Common mistake: using as the main connective
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