Artifial intelligence

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Artifial intelligence

  1. 1. “The analyticalengine has nopretensions whatever to originateany thing it can dowhat ever weknow how to orderit to perform “
  2. 2. Intelligence is theability to acquire,retrieve knowledgein a meaningfulway
  3. 3. 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.
  4. 4. What makes a computerintelligent.: Speed of computationFilteration of resultsAlgorithms:
  5. 5. Research in AI has focused onfollowing components: LEARNING REASONING: UNDERSTANDING CREATIVITY: INTUITION:
  6. 6. Why artificialintelligence:•trouble understanding specificsituations and adapting to newsituations.•improves machine behavior
  7. 7. KNOWLEDGE REPRESENTATION: facilitates inferencing use a symbol system to represent a domain of discourse give meaning to the sentences in the logic.
  8. 8. EXAMPLE:CANNIBAL-MISSIONARY PROBLEM the importance of knowledge. solved by intelligent algorithms
  9. 9. NEED FOR FORMAL LANGUAGES: “The boy saw a girl with a telescope” Symbolic logic is a syntactically unambigious knowledge representation language
  10. 10. KNOWLEDGE REPRESENTATIONTECHNIQUES IN AI: PROPOSITIONAL LOGICdeclarative statement ~ -> Negation → -> implication ↔ -> implies and implied by v -> disjunction ^ -> Conjunction
  11. 11. 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
  12. 12. 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)
  13. 13. 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
  14. 14. 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
  15. 15. .Frames:Distinguish– statements about an object’srelationships– properties of the object
  16. 16. 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
  17. 17. 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)
  18. 18. Nonmonotonic Reasoning:Collection of true facts neverdecreasesFacts changes with time
  19. 19. Principles of NMRs : If x is not known, then conclude yIf x cannot be proved, then conclude ye.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 meetingdependency-directed backtracking
  20. 20. 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.
  21. 21. 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
  22. 22. Fundamental Problems of AIlimited acquisition of informationby itselfencodable in “informationstructures”
  23. 23. CONCLUSION: Finally we are clear about thevast spread of the artificialintelligence in various fields andthe area of knowledgerepresentation in artificialintelligence.
  24. 24. THANK YOU

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