Informed (Heuristic) Search

Informed search algorithms utilize problem-specific knowledge to guide the search, making them more efficient than uninformed methods. This knowledge, known as a heuristic, estimates the cost to reach the goal from a given state. While heuristics do not guarantee the best solution, they often provide good solutions within a reasonable timeframe.

Key Characteristics of Informed Search

  1. Uses Heuristics: Guides the search process based on domain knowledge.

  2. More Efficient: Requires fewer node expansions compared to uninformed methods.

  3. Handles Complex Problems: Solves problems that are computationally infeasible for uninformed search.

Types of Informed Search Algorithms

  1. Greedy Search

  2. A* Tree Search

  3. A* Graph Search

  4. Iterative Deepening A* (IDA)

  5. Beam Search

Let's take a closer look at all these types.

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