“The analyticalengine has nopretensions whatever to originateany thing it can dowhat ever weknow how to orderit to perform “
Intelligence is theability to acquire,retrieve knowledgein a meaningfulway
Artificial intelligence (AI) isthe intelligence of machinesand the branch of computerscience that aims to create it.the study and design of intelligentagents" where an intelligentagent is a system that perceives itsenvironment and takes actions thatmaximize its chances of success.
What makes a computerintelligent.: Speed of computationFilteration of resultsAlgorithms:
Research in AI has focused onfollowing components: LEARNING REASONING: UNDERSTANDING CREATIVITY: INTUITION:
Why artificialintelligence:•trouble understanding specificsituations and adapting to newsituations.•improves machine behavior
KNOWLEDGE REPRESENTATION: facilitates inferencing use a symbol system to represent a domain of discourse give meaning to the sentences in the logic.
EXAMPLE:CANNIBAL-MISSIONARY PROBLEM the importance of knowledge. solved by intelligent algorithms
NEED FOR FORMAL LANGUAGES: “The boy saw a girl with a telescope” Symbolic logic is a syntactically unambigious knowledge representation language
KNOWLEDGE REPRESENTATIONTECHNIQUES IN AI: PROPOSITIONAL LOGICdeclarative statement ~ -> Negation → -> implication ↔ -> implies and implied by v -> disjunction ^ -> Conjunction
SYNTAX:syntax= how a sentence looks likeSentence -> AtomicSentence | ComplexSentenceAtomicSentence -> T(RUE) | F(ALSE) | SymbolsComplexSentence -> ( Sentence ) | NOT Sentence |Connective -> AND | OR | IMPLIES | EQUIV(ALENT)Precedence: NOT AND OR IMPLIES EQUIVALENTconjunction disjunction implication equivalencenegation
Semantics:semantics= what a sentence meansinterpretation: assigns each symbol a truth value, either t(rue) or f(alse) the truth value of T(RUE) is t(rue) the truth value of F(ALSE) is f(alse)
Terminology:A sentence is valid if it is True under allpossible assignments ofTrue/False to its propositional variables (e.g.P_:P) Valid sentences are also referred to astautologies
Semantic Networks:l Graph structures that encode taxonomicknowledge of objects and their properties.– objects represented as nodes– relations represented as labeled edgesl Inheritance = form of inference in whichsubclasses inherit properties ofsuperclasses
.Frames:Distinguish– statements about an object’srelationships– properties of the object
NORMAL Form in predicate LOGICRule:-1. Replace and by using equivalentformulas.2. Repeated use of negation~(~p)=F.Demorgan’s law to bring negation infront of each atom.~ (GF)= ~G~F.Use ~x F(x)= x~F(x) and~xF(x) = x~F(x) Then use all the equivalent expressions tobring the quantities in front of the expressions
Resolution in predicate LOGIC:i) R(a)ii) R(x) M(x,b)First replace a in place of x in 2nd premise and conclude M(a,b).e.g:Marcus was a man. Man (marcus)Marcus was a Pompeian. Pompeian (Marcus)Caesar was a ruler. Ruler (Caesar)
Nonmonotonic Reasoning:Collection of true facts neverdecreasesFacts changes with time
Principles of NMRs : If x is not known, then conclude yIf x cannot be proved, then conclude ye.g. 1: To build a program that generates asolution to a fairly a simple problem.e.g. 2: To find out a time at which three busycan all attain a meetingdependency-directed backtracking
Necessity of NMR: The presence of incomplete information requires default reasoning. A changing world must be decided by a changing database. Generating a complete solution to a problem may require temporary assumption about partial solution.
PROCEDURAL Vs DECLARATIVEKNOWLEDGE:Advantages of declarative knowledge are: The ability to use knowledge in ways thatthe system designer did not forseeAdvantages of procedural knowledge are: Possibly faster usage
Fundamental Problems of AIlimited acquisition of informationby itselfencodable in “informationstructures”
CONCLUSION: Finally we are clear about thevast spread of the artificialintelligence in various fields andthe area of knowledgerepresentation in artificialintelligence.