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CS621: Artificial Intelligence

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Learn about circuit verification, resolution trees, predicate calculus, Prolog, backward chaining, and heuristic strategies in artificial intelligence. Understand systematic inferencing, knowledge representation, and application in puzzles and robotics.

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CS621: Artificial Intelligence

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  1. CS621: Artificial Intelligence Pushpak BhattacharyyaCSE Dept., IIT Bombay Lecture 24– Circuit Verification with Predicate Calculus; Prolog start 23rd September, 2010

  2. Resolution Tree

  3. Search in resolution • Heuristics for Resolution Search • Goal Supported Strategy • Always start with the negated goal • Set of support strategy • Always one of the resolvents is the most recently produced resolute

  4. Inferencing in Predicate Calculus • Forward chaining • Given P, , to infer Q • P, match L.H.S of • Assert Q from R.H.S • Backward chaining • Q, Match R.H.S of • assert P • Check if P exists • Resolution – Refutation • Negate goal • Convert all pieces of knowledge into clausal form (disjunction of literals) • See if contradiction indicated by null clause can be derived

  5. P • converted to Draw the resolution tree (actually an inverted tree). Every node is a clausal form and branches are intermediate inference steps.

  6. Resolution • Theoretical basis of Resolution • Resolution proves something and the answer to the question is a side effect

  7. Resolution (cont …) • Theoretical basis of Resolution • Using Semantic Tree Contradiction

  8. Terminology • Pair of clauses being resolved is called the Resolvents. The resulting clause is called the Resolute. • Choosing the correct pair of resolvents is a matter of search.

  9. Application of Predicate Calculus Systematic Inferencing Knowledge Representation Puzzles • -- Circuit Verification • - Robotics • - Intelligent DB

  10. Circuit Verification • Does the circuit meet the specs? • Are there faults? • are they locatable?

  11. Example : 2-bit full adder X1, X2: inputs; C1: prev. carry; C2: next carry; Y: output

  12. K-Map Y x2x1 00 01 10 11 c1 0 1

  13. K-Map (contd..) C2 x2x1 00 01 10 11 c1 0 1

  14. Circuit

  15. Verification • First task (most difficult) • Building blocks : predicates • Circuit observation : Assertion on terminals

  16. Predicates & Functions

  17. Alternate Full Adder Circuit

  18. Functions Predicates • connected(t1,t2): true, if terminal t1 and t2 are connected type(X) : takes values AND, OR NOT and XOR, where X is a gate. in(n, X) : the value of signal at the nth input of gate X. out(X) : output of gate X. signal(t) : state at terminal t = 1/0

  19. General Properties • Commutativity: ∀t1,t2 [connected(t1,t2) → connected(t2,t1)] • By definition of connection: ∀t1,t2 [connected(t1,t2) → { signal(t1) = signal(t1)}]

  20. Gate properties • OR definition: • AND definition:

  21. Gate properties contd… • XOR definition: • NOT definition:

  22. Some necessary functions no_of_input(x), takes integer values Count_ls(x), returns no. of 1s in the input of X

  23. Circuit specific properties Connectivity: connected(x1, in(1,A1)) connected(x1, in(2, A1)) connected(out(A1), in(1, A2)) connected(c1, in(2, A2)) connected(y, out(A2)) … Circuit elements: type(A1) = XOR, type(A2) = XOR, type(A3) = AND …

  24. Circuit

  25. Prolog

  26. Introduction • PROgramming in LOGic • Emphasis on what rather than how Problem in Declarative Form LogicMachine Basic Machine

  27. Prolog’s strong and weak points • Assists thinking in terms of objects and entities • Not good for number crunching • Useful applications of Prolog in • Expert Systems (Knowledge Representation and Inferencing) • Natural Language Processing • Relational Databases

  28. A Typical Prolog program Compute_length ([],0). Compute_length ([Head|Tail], Length):- Compute_length (Tail,Tail_length), Length is Tail_length+1. High level explanation: The length of a list is 1 plus the length of the tail of the list, obtained by removing the first element of the list. This is a declarative description of the computation.

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