Heuristic ( /hjʉˈrɪstɨk/; or heuristics; Greek: "Εὑρίσκω", "find" or "discover") refers to experience-based techniques for problem solving, learning, and discovery. Where an exhaustive search is impractical, heuristic methods are used to speed up the process of finding a satisfactory solution. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, or common sense.

In more precise terms, heuristics are strategies using readily accessible, though loosely applicable, information to control problem solving in human beings and machines.

The most fundamental heuristic is trial and error, which can be used in everything from matching nuts and bolts to finding the values of variables in algebra problems.

Here are a few other commonly used heuristics, from George Pólya's 1945 book, How to Solve It:

In psychology, heuristics are simple, efficient rules, hard-coded by evolutionary processes or learned, which have been proposed to explain how people make decisions, come to judgments, and solve problems, typically when facing complex problems or incomplete information. These rules work well under most circumstances, but in certain cases lead to systematic errors or cognitive biases.^{[citation needed]}

Gerd Gigerenzer (born September 3, 1947, Wallersdorf) is a German psychologist who has studied the use of bounded rationality and heuristics in decision making, especially in medicine. A critic of the work of Daniel Kahneman and Amos Tversky, he argues that heuristics should not lead us to conceive of human thinking as riddled with irrational cognitive biases, but rather to conceive rationality as an adaptive tool that is not identical to the rules of formal logic or the probability calculus.

With Daniel Goldstein he first theorized the recognition heuristic.

He has written several books on the subject of heuristics and decision making, including Simple Heuristics That Make Us Smart (1999), and Bounded Rationality: The Adaptive Toolbox (2001) with Reinhard Selten. His two books for a lay audience, Reckoning with Risk: Learning to Live with Uncertainty (2002, published in the U.S. as Calculated Risks: How to Know When Numbers Deceive You), and Gut Feelings: The Intelligence of the Unconscious (2007), have been translated into 18 languages. "Rationality for Mortals", his most recent book, investigates decisions under limited time and information. He has trained U.S. Federal Judges, German physicians, and top managers in decision making and understanding risks and uncertainties.

Richard Phillips Feynman ( /ˈfaɪnmən/; May 11, 1918 – February 15, 1988) was an American physicist known for his work in the path integral formulation of quantum mechanics, the theory of quantum electrodynamics, and the physics of the superfluidity of supercooled liquid helium, as well as in particle physics (he proposed the parton model). For his contributions to the development of quantum electrodynamics, Feynman, jointly with Julian Schwinger and Sin-Itiro Tomonaga, received the Nobel Prize in Physics in 1965. He developed a widely used pictorial representation scheme for the mathematical expressions governing the behavior of subatomic particles, which later became known as Feynman diagrams. During his lifetime, Feynman became one of the best-known scientists in the world. In a 1999 poll of 130 leading physicists worldwide by the British journal Physics World he was ranked as one of the ten greatest physicists of all time.

He assisted in the development of the atomic bomb and was a member of the panel that investigated the Space Shuttle Challenger disaster. In addition to his work in theoretical physics, Feynman has been credited with pioneering the field of quantum computing, and introducing the concept of nanotechnology. He held the Richard Chace Tolman professorship in theoretical physics at the California Institute of Technology.

Eliezer Shlomo Yudkowsky (born September 11, 1979) is an American artificial intelligence researcher concerned with the singularity and an advocate of friendly artificial intelligence, living in Redwood City, California.

Yudkowsky did not attend high school and is an autodidact, having no formal education in computer science or artificial intelligence. He co-founded the nonprofit Singularity Institute for Artificial Intelligence (SIAI) in 2000 and continues to be employed as a full-time Research Fellow there.

Yudkowsky's research focuses on Artificial Intelligence theory for self-understanding, self-modification, and recursive self-improvement (seed AI); and also on artificial-intelligence architectures and decision theories for stably benevolent motivational structures (Friendly AI, and Coherent Extrapolated Volition in particular). Apart from his research work, Yudkowsky has written explanations of various philosophical topics in non-academic language, particularly on rationality, such as "An Intuitive Explanation of Bayes' Theorem".