Heuristic Computer Program
- Uses practical, approximate, or educated guesses to produce solutions when exact methods are impractical.
- Favours speed and practicality over guaranteed optimality or accuracy.
- Common in tools like spell checkers and search engines.
Definition
Section titled “Definition”A heuristic computer program is a type of algorithm that uses practical, approximate, or educated guesses to solve problems. These programs are designed to provide quick solutions to complex problems, even if the solutions may not be the most accurate or optimal.
Explanation
Section titled “Explanation”Heuristic programs apply rules of thumb or educated assumptions (heuristics) instead of exhaustive calculations, enabling faster solutions for complex or large-scale problems. Because they rely on approximations, their results can be quick but are not always optimal or perfectly accurate. Examples of the heuristic strategies described include comparing inputs against a dictionary of common items, ranking items by relevance using multiple factors, and prioritizing computationally inexpensive indicators of quality.
Examples
Section titled “Examples”Spell checker
Section titled “Spell checker”A spell checker uses a dictionary of common words and their correct spellings to check words in a document. When a word is typed that is not in the dictionary, the spell checker will use heuristics, such as comparing the word to similar-sounding words in the dictionary, to suggest a possible correct spelling.
Search engine
Section titled “Search engine”Search engines use heuristics to determine the relevance and importance of web pages based on keywords and other factors, such as the number of other websites that link to the page. The search engine then uses this information to rank the pages and display the most relevant results to the user’s search query.
Use cases
Section titled “Use cases”Heuristic programs are widely used in many areas of computer science, including artificial intelligence, natural language processing, and optimization algorithms. They are particularly useful when the amount of data or the complexity of a problem makes exhaustive algorithms impractical.
Notes or pitfalls
Section titled “Notes or pitfalls”- Heuristic solutions can be incorrect or suboptimal: a spell checker may suggest an incorrect correction, and a search engine may display irrelevant results.
- The trade-off for speed and practicality is that heuristics are based on educated guesses and assumptions, not guaranteed optimal methods.
Related terms
Section titled “Related terms”- Algorithm
- Heuristics
- Artificial intelligence
- Natural language processing
- Optimization algorithms
- Spell checker
- Search engine