1. Problem Definition

The first step involves a clear and structured understanding of the problem. This includes:

  •  Initial State: Where the system starts
  •  Goal State: The desired outcome
  •  Operators: Actions that transition between states
  •  Constraints: Conditions that must be satisfied

2. Search Space and State Space

The search space encompasses all possible configurations of the system from the initial to the goal state. State space is the subset navigated through defined rules. Efficient problem solvers use intelligent search algorithms to navigate this space.

 Examples of Problems in Artificial Intelligence

In today’s fast-paced digitized world, artificial intelligence techniques are used widely to automate systems that can use resources and time efficiently. Some of the well-known problems experienced in everyday life are games and puzzles. Using AI techniques, we can solve these problems efficiently. In this sense, some of the most common problems resolved by AI are:

  •  Travelling Salesman Problem
  •  Tower of Hanoi Problem
  •  Water-Jug Problem
  •  N-Queen Problem
  •  Chess
  •  Sudoku
  •  Crypt-arithmetic Problems
  •  Magic Squares
  •  Logical Puzzles and so on.