What is heuristics?

Heuristics refers to an analytical procedure of arriving at conclusions and solutions with limited knowledge. The inferred statements may deviate from the optimal solution. The comparison between the optimal solution and the solution of the heuristic procedure determines the quality of the heuristic procedures.

The best-known heuristic methods include trial and error algorithms. They also include statistical evaluations of certain random samples and exclusion procedures. Such procedures are based on experience already gained.

Through heuristics it is possible that a Optimum solution in a short time can be found. In this way, shortened computational paths are used to perform calculations more quickly. This has made it possible for programmes like Deep Blue or AlphaGo be able to beat leading professional players in chess and Go respectively.

Areas of application for heuristics can be found in speech and face recognition, in character recognition (OCR), in the Data mining and in general knowledge-based systems.

How is a heuristic procedure defined?

In the more recent philosophy of science, heuristics are as an assessment criterion for theories, as well as for entire science programmes (paradigm) and are of particular importance. However, it is not exclusively the information content that is evaluated, but above all the inherent potential for further development of the state of knowledge.

Heuristic methods can provide a procedure for solving general problems. Especially when no clear solution strategy is known, they can be used successfully. They are primarily based on subjective experience. Traditional behavioural patterns can also play a role.

They can be used especially for problem areas that are poorly structured or difficult to grasp. In this way mathematical problems elegantly solved and their time required considerably reduced can be used. Such solution methods can be used without proof of convergence for problems for which no converging methods exist.

What types of heuristics are there?

Numerous different methods are used in science. Their structure usually depends on the area of application in which they are used.

  • Take-the-Best heuristic procedures exploit the best possible strategy.
  • Recognition heuristics are based on the recognition effect.
  • Availability heuristics are based on individual memories.
  • Representational heuristics have a prototype and allow inferences to be made in the case of similarities.
  • Anchor heuristics can possibly benefit from the anchor effect, whereby arbitrarily chosen anchors influence people in their decision-making process.
  • The expert heuristic can use expert knowledge.
  • Sympathy heuristic evaluates statements and appearance of persons.
  • The consensus heuristic pays attention to majority opinions.
  • In Operations Research, heuristics exist as opening procedures, as improvement procedures, as incompletely exact procedures and as compound procedures. A distinction is made between problem-specific and universal heuristics.
  • There are also metaheuristics, such as the ant algorithm, different types of evolutionary algorithms, or simulated annealing, tabu search and also variable neighbourhood search.