Heuristic (psychology)

Heuristics is the process by which humans use mental short cuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability. The economist and cognitive psychologist Herbert A. Simon introduced the concept of heuristics in the 1950s, suggesting there were limitations to rational decision making. In the 1970s, psychologists Amos Tversky and Daniel Kahneman added to the field with their research on cognitive bias. It was their work that introduced specific heuristic models, a field which has only expanded since. While some argue that pure laziness is behind the heuristics process, others argue that it can be more accurate than decisions based on every known factor and consequence, the less-is-more effect. Herbert A. Simon formulated one of the first models of heuristics, known as satisficing. His more general research program posed the question of how humans make decisions when the conditions for rational choice theory are not met, that is how people decide under uncertainty. Simon is also known as the father of bounded rationality, which he understood as the study of the match (or mismatch) between heuristics and decision environments. This program was later extended into the study of ecological rationality. In the early 1970s, psychologists Amos Tversky and Daniel Kahneman took a different approach, linking heuristics to cognitive biases.

Data-driven 1D wave propagation for site response analysis

Jean-François Molinari, Antonio Joaquin Garcia Suarez, Sacha Zenon Wattel

Prediction of ground motion triggered by earthquakes is a prime concern for both the seismology community and geotechnical earthquake engineering one. The subfield occupied with such a problem is termed site response analysis (SRA), its one-dimensional fla ...

WILEY2023

Heuristic Estimation of the Vacuum Energy Density of the Universe: Part II-Analysis Based on Frequency Domain Electromagnetic Radiation

Data-driven 1D wave propagation for site response analysis

Heuristic Estimation of the Vacuum Energy Density of the Universe: Part II-Analysis Based on Frequency Domain Electromagnetic Radiation

Data-driven 1D wave propagation for site response analysis