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Problem Solving in Artificial Intelligence | Fourth Semester | BSc.CSIT (TU)

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problem solvingProblem Solving | Fourth Semester
Second year | Tribhuvan University (TU)
Subject: Cognitive Science | BSc.CSIT

Problem Solving in Artificial Intelligence
Problem solving, particularly in artificial intelligence, may be characterized as a systematic search through a range of possible actions in order to reach some predefined goal or solution. Problem-solving methods divide into special purpose and general purpose. A special-purpose method is tailor-made for a particular problem and often exploits very specific features of the situation in which the problem is embedded. In contrast, a general-purpose method is applicable to a wide variety of problems. One general-purpose technique used in AI is means-end analysis—a step-by-step, or incremental, reduction of the difference between the current state and the final goal.

Four general steps in problem solving:

  • Goal formulation

What are the successful world states

  • Problem formulation

What actions and states to consider given the goal

  • Search

Determine the possible sequence of actions that lead to the states of known values and then choosing the best sequence.

  • Execute

Give the solution perform the actions.

Problem formulation:
A problem is defined by:

  • An initial state: State from which agent start
  • Successor function: Description of possible actions available to the agent.
  • Goal test: Determine whether the given state is goal state or not
  • Path cost: Sum of cost of each path from initial state to the given state.

A solution is a sequence of actions from initial to goal state. Optimal solution has the lowest path cost.

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