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CS 344 Artificial Intelligence By Prof: Pushpak Bhattacharya Class on 17/Jan/2007

CS 344 Artificial Intelligence By Prof: Pushpak Bhattacharya Class on 17/Jan/2007. Search building blocks. State Space : Graph of states (Express constraints and parameters of the problem) Operators : Transformations applied to the states. Start state : S 0 (Search starts from here)

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CS 344 Artificial Intelligence By Prof: Pushpak Bhattacharya Class on 17/Jan/2007

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  1. CS 344 Artificial Intelligence By Prof: Pushpak Bhattacharya Class on 17/Jan/2007

  2. Search building blocks • State Space : Graph of states (Express constraints and parameters of the problem) • Operators : Transformations applied to the states. • Start state : S0(Search starts from here) • Goal state : {G} - Search terminates here. • Cost : Effort involved in using an operator. • Optimal path : Least cost path

  3. Examples Problem 1 : 8 – puzzle 1 2 3 4 3 6 1 4 2 8 6 5 5 8 7 7 S0 G Tile movement represented as the movement of the blank space. Operators: L : Blank moves left R : Blank moves right U : Blank moves up D : Blank moves down C(L) = C(R) = C(U) = C(D) = 1

  4. Problem 2: Missionaries and Cannibals R boat River boat L Missionaries Cannibals Missionaries Cannibals • Constraints • The boat can carry at most 2 people • On no bank should the cannibals outnumber the missionaries

  5. State : <#M, #C, P> #M = Number of missionaries on bank L #C = Number of cannibals on bank L P = Position of the boat S0 = <3, 3, L> G = < 0, 0, R > Operations M2 = Two missionaries take boat M1 = One missionary takes boat C2 = Two cannibals take boat C1 = One cannibal takes boat MC = One missionary and one cannibal takes boat

  6. <3,3,L> C2 MC <3,1,R> <2,2,R> <3,3,L> Partial search tree

  7. Problem 3 B B W W W B G: States where no B is to the left of any W Operators: 1) A tile jumps over another tile into a blank tile with cost 2 2) A tile translates into a blank space with cost 1 All the three problems mentioned above are to be solved using A*

  8. Where is AI coming into picture in all these!! AI involves search of state space Vision NLP • Search • Reasoning • Learning • Knowledge Robotics Expert Systems Planning

  9. Computer Vision Left retina Right retina Problem: Find the corresponding cells in the two retinae; this is a search problem. This information is used for identifying the depth of objects and forming the 3D picture of objects

  10. Robotic Planning C A B B A C Problem: What sequence of arm moves should be followed to reach a particular configuration; again a search problem.

  11. NLP Search needed amongst possibilities to arrive at the right meaning. e.g: “The camera man shot the batsman when he was near the chairman of the selection committee” Different meanings for this sentence. These are to be inferred 1) Who is near chairman 2) Meaning of shot 3) ..... 4) ..... ...... There can be 14 different meanings for the sentence above. Which one to choose as the actual meaning? Another example: “Time flies like an arrow”

  12. Machine Learning Mon Tue Wed Thu Fri R1 R2 R3 R4 Eating at corresponding restaurant on that day caused stomach problem Problem: Infer a hypothesis which generalizes the properties of restaurants on different days, in terms of causing stomach problems

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