Informed (Heuristic) Search Techniques

Informed search leverages heuristics — intelligent guesses — to guide the search more efficiently toward the goal.
Examples include:

• Greedy Best-First Search: Selects the node that appears closest to the goal.
• A* Algorithm: Combines actual cost and heuristic estimates for optimal results.
• Hill Climbing: Continuously moves toward higher-value states.
• Beam Search: Keeps only a fixed number of best candidates at each step.

Heuristic methods are especially useful in large or complex state spaces like robot pathfinding, game playing, and optimization problems.
They reduce computation time while maintaining accuracy — balancing intelligence and efficiency.