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Simple Heuristics (simple + heuristic)

Distribution by Scientific Domains
Humanities and Social Sciences33%

Selected Abstracts

Information search in heuristic decision making

APPLIED COGNITIVE PSYCHOLOGY, Issue 4 2010
Mandeep K. Dhami
Simple heuristics of the type introduced by Gigerenzer, Todd, and The ABC Research Group (1999) embody principles for information search, stop and decision making. These heuristics suggest that such processes are simple. In an analysis of general practitioners' (GPs) information search and decision-making behaviour when prescribing a lipid lowering drug, we examined whether information search was simple, and whether a heuristic that predicts a simple decision-making process was also accurate at describing information search. We found that GPs' information search behaviour was simple in that it demonstrated characteristics of the matching heuristic (e.g. stopping rule). In addition, although the matching heuristic which correctly predicted on average 75% of GPs' decisions used significantly fewer cues on average than the GPs did in the information search task, it was reasonably accurate in describing order of information search. These findings have implications for the validity of simple heuristics describing both information search and decision making. Copyright © 2009 John Wiley & Sons, Ltd. [source]

The probabilistic analysis of a greedy satisfiability algorithm

RANDOM STRUCTURES AND ALGORITHMS, Issue 4 2006
Alexis C. Kaporis
On input a random 3-CNF formula of clauses-to-variables ratio r3 applies repeatedly the following simple heuristic: Set to True a literal that appears in the maximum number of clauses, irrespective of their size and the number of occurrences of the negation of the literal (ties are broken randomly; 1-clauses when they appear get priority). We prove that for r3 < 3.42 this heuristic succeeds with probability asymptotically bounded away from zero. Previously, heuristics of increasing sophistication were shown to succeed for r3 < 3.26. We improve up to r3 < 3.52 by further exploiting the degree of the negation of the evaluated to True literal. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006 [source]

Strategies for the Curiosity-Driven Museum Visitor

CURATOR THE MUSEUM JOURNAL, Issue 4 2004
Jay Rounds
ABSTRACT Tracking studies show that museum visitors typically view only 20 to 40 percent of an exhibition. Current literature states that this partial use sub-optimizes the educational benefit gained by the visitor, and that skilled visitors view an exhibition comprehensively and systematically. Contrary to that viewpoint, this paper argues that partial use of exhibitions is an intelligent and effective strategy for the visitor whose goal is to have curiosity piqued and satisfied. By using analytical approaches derived from "optimal foraging theory" in ecology, this paper demonstrates that the curiosity-driven visitor seeks to maximize the Total Interest Value of his or her museum visit. Such visitors use a set of simple heuristics to find and focus attention only on exhibit elements with high interest value and low search costs. Their selective use of exhibit elements results in greater achievement of their own goals than would be gained by using the exhibition comprehensively. [source]

Interests and information in referendum voting: An analysis of Swiss voters

EUROPEAN JOURNAL OF POLITICAL RESEARCH, Issue 6 2002
Thomas Christin
Referendums impose considerable informational demands on voters. Recent theoretical and empirical research has emphasized the different shortcuts and heuristics they may employ in deciding how to vote. Relying on a substantial series of votes at the national level in Switzerland, we provide empirical tests on how Swiss voters cope with the informational demands in referendum voting. We combine simple heuristics, like partisan cues and endorsements, with indicators of instrumental interests to explain citizens' choices in a series of votes. [source]

A Genetic Algorithm Hybrid for Constructing Optimal Response Surface Designs

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2004
David Drain
Abstract Hybrid heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective, and simple heuristics like simulated annealing fail to find good solutions. One such heuristic hybrid is GASA (genetic algorithm,simulated annealing), developed to take advantage of the exploratory power of the genetic algorithm, while utilizing the local optimum exploitive properties of simulated annealing. The successful application of this method is demonstrated in a difficult design problem with multiple optimization criteria in an irregularly shaped design region. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Information search in heuristic decision making

APPLIED COGNITIVE PSYCHOLOGY, Issue 4 2010
Mandeep K. Dhami
Simple heuristics of the type introduced by Gigerenzer, Todd, and The ABC Research Group (1999) embody principles for information search, stop and decision making. These heuristics suggest that such processes are simple. In an analysis of general practitioners' (GPs) information search and decision-making behaviour when prescribing a lipid lowering drug, we examined whether information search was simple, and whether a heuristic that predicts a simple decision-making process was also accurate at describing information search. We found that GPs' information search behaviour was simple in that it demonstrated characteristics of the matching heuristic (e.g. stopping rule). In addition, although the matching heuristic which correctly predicted on average 75% of GPs' decisions used significantly fewer cues on average than the GPs did in the information search task, it was reasonably accurate in describing order of information search. These findings have implications for the validity of simple heuristics describing both information search and decision making. Copyright © 2009 John Wiley & Sons, Ltd. [source]