Homo Heuristicus: Why Biased Minds Make Better Inferences Gerd Gigerenzer, Henry Brighton Max Planck Institute for Human Development Abstract: Heuristics are efficient cognitive processes that ignore information. Contrary to the belief that less processing reduces accuracy, heuristics can improve accuracy by using less information, computation, and time. The paper reviews major progress in heuristic research: (a) less-is-more effects; (b) ecological rationality of heuristics; (c) computational models of heuristics; (d) a systematic theory of heuristics; and (e) empirical methodology for heuristic use. Homo heuristicus has a biased mind that ignores part of the available information but handles uncertainty more efficiently than unbiased minds. Animals and humans use heuristics to solve adaptive problems. Examples include ants measuring cavity size and peahens choosing mates. Heuristics are simple and efficient, and their accuracy is due to exploiting evolved mental abilities and environmental structures. The term "heuristic" comes from Greek, meaning "serving to find out or discover." Heuristics are indispensable for finding proofs, while analysis is needed to check validity. In the 1950s, Herbert Simon proposed that people satisfy rather than maximize. Heuristics allow for fast and frugal decisions. In the 1970s, heuristics were seen as leading to errors, but recent research shows that less information can lead to higher accuracy. The accuracy-effort trade-off is not always valid, and less-is-more effects can occur. Heuristics can be more accurate than complex procedures by exploiting evolved mental abilities and environmental structures. A systematic science of heuristics has emerged, showing that heuristics can be more accurate than complex strategies in certain environments. The ecological rationality of heuristics is an alternative explanation, showing how less-is-more effects emerge from the bias-variance dilemma. The paper discusses the development of computational models of heuristics, the ecological rationality of heuristics, and the bias-variance dilemma. It also discusses the importance of understanding the conditions under which heuristics are more accurate than complex strategies. The paper concludes that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environment. The paper also discusses the importance of understanding the bias-variance dilemma in explaining the success of heuristics. The paper shows that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environment. The paper also discusses the importance of understanding the bias-variance dilemma in explaining the success of heuristics. The paper concludes that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environmentHomo Heuristicus: Why Biased Minds Make Better Inferences Gerd Gigerenzer, Henry Brighton Max Planck Institute for Human Development Abstract: Heuristics are efficient cognitive processes that ignore information. Contrary to the belief that less processing reduces accuracy, heuristics can improve accuracy by using less information, computation, and time. The paper reviews major progress in heuristic research: (a) less-is-more effects; (b) ecological rationality of heuristics; (c) computational models of heuristics; (d) a systematic theory of heuristics; and (e) empirical methodology for heuristic use. Homo heuristicus has a biased mind that ignores part of the available information but handles uncertainty more efficiently than unbiased minds. Animals and humans use heuristics to solve adaptive problems. Examples include ants measuring cavity size and peahens choosing mates. Heuristics are simple and efficient, and their accuracy is due to exploiting evolved mental abilities and environmental structures. The term "heuristic" comes from Greek, meaning "serving to find out or discover." Heuristics are indispensable for finding proofs, while analysis is needed to check validity. In the 1950s, Herbert Simon proposed that people satisfy rather than maximize. Heuristics allow for fast and frugal decisions. In the 1970s, heuristics were seen as leading to errors, but recent research shows that less information can lead to higher accuracy. The accuracy-effort trade-off is not always valid, and less-is-more effects can occur. Heuristics can be more accurate than complex procedures by exploiting evolved mental abilities and environmental structures. A systematic science of heuristics has emerged, showing that heuristics can be more accurate than complex strategies in certain environments. The ecological rationality of heuristics is an alternative explanation, showing how less-is-more effects emerge from the bias-variance dilemma. The paper discusses the development of computational models of heuristics, the ecological rationality of heuristics, and the bias-variance dilemma. It also discusses the importance of understanding the conditions under which heuristics are more accurate than complex strategies. The paper concludes that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environment. The paper also discusses the importance of understanding the bias-variance dilemma in explaining the success of heuristics. The paper shows that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environment. The paper also discusses the importance of understanding the bias-variance dilemma in explaining the success of heuristics. The paper concludes that heuristics can be more accurate than complex strategies in certain environments, and that the success of heuristics depends on the match between the heuristic and the environment