Heuristic - 105
In artificial intelligence and computer science, a "heuristic" is a problem-solving strategy that uses practical or "rule-of-thumb" methods to find solutions that are not necessarily guaranteed to be optimal or perfect, but are often good enough for practical purposes.
Heuristics are often used in situations where there is no known algorithmic solution or where finding an exact solution is computationally intractable. Instead, heuristics rely on experience and intuition to guide the search for a solution, often trading off accuracy for efficiency.
For example, in a game of chess, a heuristic-based approach might involve evaluating the current board position and choosing a move that maximizes the chances of winning based on heuristics such as the strength of the pieces, the control of key squares, and the proximity to the opponent's king. This approach may not always lead to the optimal move, but it can be effective in practice and is often used by both human and computer players.
Another example of a heuristic-based approach is the "greedy" algorithm, which makes locally optimal choices at each step of a problem with the hope that they will lead to a globally optimal solution. While this strategy does not always guarantee an optimal solution, it can be effective in certain cases, such as finding a minimum spanning tree in a graph.
Overall, heuristics are an important tool in artificial intelligence and computer science for finding practical solutions to complex problems, and they can be used in a variety of domains, from optimization and search to game playing and decision making.