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I ntroduction. Defining the Problem as a State Space Search. Defining the Problem as a State Space Search. The state space search representation forms the basis of most of the AI method. Its structure corresponds to the structure problem solving in two important ways:

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  1. Introduction • Defining the Problem as a State Space Search

  2. Defining the Problem as a State Space Search The state space search representation forms the basis of most of the AI method. Its structure corresponds to the structure problem solving in two important ways: • If allows for a formal definition of a problem as the need to convert some given situation into some desired situation using a set of permissible operation. • It permits us to define the process of solving a particular problem as a combination of known techniques and search. The general technique of exploring the space to try to find some path from the current state to a good state.

  3. Defining the Problem as a State Space Search(cont..) • Search is very important process in the solution of hard problem for which no more direct technique are available. • In order to provide a formal description of a problem it is necessary to do the following things: • Define a state space that contains all the possible configurations of the relevant objects. • Specify one or more states within that space that describe possible situation from which the problem solving process may start. These states are called the initial states. • Specify one or more states that would be acceptable as solution to the problem. These states are called goal states. • Specify a set of rules that describe the actions (operators) available.

  4. Water Jug Problem: • Problem: You are given two jugs. A 4 gallon one and a 3 gallon one. Neither has any measuring marker on it. There is a pump that can be used to fill the jugs with water. How can you get exactly 2 gallons of water into the 4 gallon jug? • Solution: The state space for this problem can be described as a set of ordered pair of integers (x, y) such that x = 0, 1, 2, 3, 4 and y = 0, 1, 2, 3. x represent the numbers of gallon of water in 4 gallon jug and y represent the numbers of gallon of water in 3 gallon jug. The start state is (0, 0). The goal state is (2, n) for any value of n because the problem does not specify how many gallon need to be in the 3 gallon jug.

  5. Production Rules of WJ Problem

  6. Assumptions •  We have assumed that we can fill a jug from the pump and we can pour water out of a jug onto the ground. There are no measuring device: • Sample Solution:

  7. Production Systems Production system provide the structure for solving the AI problem. It consist of : •  A set of rules each consisting of a left side determines the applicability and right side that describes the operation to be performed. • One or more knowledge/ database that convert whatever information is appropriate for the particular task. • A control strategy that specify the order in which the rules will be compared to the database and a way of resolving the conflicts that arise when several rules match at once. • A rule applier

  8. Control Strategies Control Strategy deal with how to decide which rule to apply next during the process of searching for a solution to a problem because it may happen more than one rule will have its left side match the current state. •  The first requirement of a good control strategy is that because motion will never lead to a solution. • The second requirement of a good control strategy is that it be semantic. If its not semantic we may explore a particular useless sequence of operators several times before we finally find a solution. The requirement that a control strategy be semantic corresponds to the need for global motion as well as for local motion.

  9. Heuristic Search • Heuristic is a technique that improves the efficiency of a search process possibly by sacrificing claims of completeness. • Heuristic are like tour guides. • They are good to the extent that they point in generally interesting directions. • They are bad to the extent that they miss point of interest to particular individuals. • Some of heurists help to guide a search process without sacrificing any claims to completeness that the process might previously had. • Using good heuristics we can get good solution to hard problem. Heuristic search uses the Heuristic functions for finding the solution of problem.

  10. Problem Characteristics • In order to choose the most appropriate method for a particular problem it is necessary to analyze the problem using several key dimensions: • Is the problem decomposable into one of independent smaller or easier sub problem? • Can solution steps be ignored or used. • Is the problem universe predictable • Is the good solution to the problem obvious without comparison to all possible solution • Is the desired solution a state word or a path to a state. • Is a large amount of knowledge absolutely required to solve the problem or knowledge important only to constrain the search.

  11. Problem Decomposable

  12. Block World Problem

  13. Block World Problem(cont..) • Soln. There are some actions given. According to that the robot arm that can manipulate the blocks. • UNSTACK (A, B): Pick block A from its current position on Block B. The arm must be empty and block A must have no blocks on top of it. • STACK (A, B): Place block A on block B. The arm must already be holding A and the surface of B must be clear. • PICK UP(A): Pickup block A from the table and hold it. The arm must be empty and therefore must be nothing on top of block A. • PUT DOWN (A): Put block A down on the table. The arm must have been holding block A. • ON (A, B): block A is on block B. • ON TABLE (A): block A is on the table. • CLEAR(A): There is nothing on the top of block A • HOLDING(A): The arm is holding block A. • ARM EMPTY: The arm is holding nothing.

  14. There are some constraints for solving the problem. They are: • P : Precondition • D : Delete • O : Operation

  15. Solve Following

  16. Can Solution step be ignored or undone • There are generally three class of problem. • Ignorable (e.g. Theorem proving): In this solution steps can be ignored. • Recoverable (ex. 8 Puzzle) : In this solution step can be undone. • Irrecoverable (ex. Chess) : In this solution steps cannot be undone. • Recoverable problem can be solve by slightly more complicated control strategy, that does some time make mistakes. Back tracking is necessary to recover from such mistake. • Ignorable problem can be solve using simple control structure that never backtracks such control structure is easy to implement. • Irrecoverable problems will need to be solved by a system that expands a great deal of effort making each decision since the decision must be final.

  17. Is a Good Solution Absolute or Relative • Let us consider the example of predicate logic: • Marcus was a man. • Marcus was Pompeian. • Marcus was born in 40 A.D. • All men are mortal. • All Pompeian died when the volcano erupted in 79 A.D. • No mortal lives longer than 150 years. • It is now 1991 A.D. Suppose we ask the question “Is Marcus alive”. The solution of this problem is:

  18. Is a Good Solution Absolute or Relative(cont..) • 1.  Marcus was a man. • 2. All men are mortal. • 3. Marcus was born in 40 A.D. • 7. It is now 1991 A.D. • 9. Marcus’s age 1991 year. • 6. No mortal lives longer than 150 years. • 10. Marcus was dead. Or (Relative) • 7. It is now 1991 A.D. • 5. All Pompeian are dead in 79 A.D. • 11. All Pompeian are dead now. • 2. Marcus was a Pompeian. • 12. Marcus is dead.

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