• Problem Space: It is the environment in which the search takes place. (A set of states and set of operators to change those states)
  • Problem Instance: It is Initial state + Goal state
  • Problem Space Graph: It represents problem state. States are shown by nodes and operators are shown by edges.
  • Depth of a problem: Length of a shortest path or shortest sequence of operators from Initial State to goal state.
  • Space Complexity: The maximum number of nodes that are stored in memory.
  • Time Complexity: The maximum number of nodes that are created.
  • Admissibility: A property of an algorithm to always find an optimal solution.
  • Branching Factor: The average number of child nodes in the problem space graph.
  • Depth: Length of the shortest path from initial state to goal state.
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