This issue aims to portray, justify, advance, contrast, and illustrate research programs in the domain of cognitive decision-making under risk and uncertainty, where such research programs are intended to promote theories, models, or conceptual frameworks for:
• Prediction of empirical observations,
• Descriptions of empirical results, likely or rationalized to lead to predictions (e.g., models with free parameters whose values are part of a hypothesis to be tested; or cross validation of descriptive-model results);
• Generalizations of many specific empirical results;
• Normative models alternative to Expected Utility Theory (EUT)
• Replications of published results concerning any of the above.
Any of the above may concern any aspect (statistic) of empirical data, including:
• Individual or group behavior itself (e.g., prediction of people's actual choices);
• differences or difference in rankings of Individual or group behavior
• distribution of responses
for the general purpose of promoting scientific understanding of individual or collective human behavior in the domain of decision-making under risk or uncertainty. In particular, this issue may shed light on the controversy between Behavioral Economics and Cognitive Economics. The first relates to Kahneman and Tversky's program of Heuristics and Biases and the normative model of formal rationality, whereas the second is connected to Simon, Gigerenzer, and Viale's program of simple adaptive heuristics and the normative model of ecological bounded rationality. Both of which aim to improve economics on a cognitive basis.
Programs representing additional approaches may well be included. For example, Clyde Coombs' views on risky choice (including the claim that individuals have different ideal levels of risk at the same level of expected value) may point to distinct research programs and methods.
Two major programs for the study of decision making under risk and uncertainty stand out:
(a) the development of descriptive theories that adopt the EUT's conceptual framework as point of departure and proceed to explain observed violations of EUT in terms of psychological heuristics and biases. It is represented by Prospect Theory and a large body of subsequent elaborations and variations
(b) The identification of simple adaptive heuristics and the development of normative models of ecological bounded rationality. (A special case is that of the cognition-based challenge theory which foregoes reliance on concepts historically coined in the context of prescriptive economic theories, and aims at models for improving predictions of human behavior).
The main goal of the collection is to present and illustrate, within a single volume, alternative strategies for conducting research in the domain of decision-making under risk and uncertainty and to clarify the advantages and disadvantages of each of them. And, in so doing, enable the interested reader to make informed assessments of what each program aims to achieve, has achieved or can achieve.
The focus of this collection are research programs, strategies and methods in decision science. Contributors are encouraged to address questions such as: which program has proved, or is likely to prove, most significant for producing results, in basic science or in applications; how do different methods compare in their treatment of a specific decision problem; the tradeoff between over-fitting and model simplicity; and more technical issues derived from the specific approaches compared.
Article-type may vary from philosophical or technical reviews of decision science to field or laboratory research results that illustrate an advocated program or method or compare different methods.
This issue aims to portray, justify, advance, contrast, and illustrate research programs in the domain of cognitive decision-making under risk and uncertainty, where such research programs are intended to promote theories, models, or conceptual frameworks for:
• Prediction of empirical observations,
• Descriptions of empirical results, likely or rationalized to lead to predictions (e.g., models with free parameters whose values are part of a hypothesis to be tested; or cross validation of descriptive-model results);
• Generalizations of many specific empirical results;
• Normative models alternative to Expected Utility Theory (EUT)
• Replications of published results concerning any of the above.
Any of the above may concern any aspect (statistic) of empirical data, including:
• Individual or group behavior itself (e.g., prediction of people's actual choices);
• differences or difference in rankings of Individual or group behavior
• distribution of responses
for the general purpose of promoting scientific understanding of individual or collective human behavior in the domain of decision-making under risk or uncertainty. In particular, this issue may shed light on the controversy between Behavioral Economics and Cognitive Economics. The first relates to Kahneman and Tversky's program of Heuristics and Biases and the normative model of formal rationality, whereas the second is connected to Simon, Gigerenzer, and Viale's program of simple adaptive heuristics and the normative model of ecological bounded rationality. Both of which aim to improve economics on a cognitive basis.
Programs representing additional approaches may well be included. For example, Clyde Coombs' views on risky choice (including the claim that individuals have different ideal levels of risk at the same level of expected value) may point to distinct research programs and methods.
Two major programs for the study of decision making under risk and uncertainty stand out:
(a) the development of descriptive theories that adopt the EUT's conceptual framework as point of departure and proceed to explain observed violations of EUT in terms of psychological heuristics and biases. It is represented by Prospect Theory and a large body of subsequent elaborations and variations
(b) The identification of simple adaptive heuristics and the development of normative models of ecological bounded rationality. (A special case is that of the cognition-based challenge theory which foregoes reliance on concepts historically coined in the context of prescriptive economic theories, and aims at models for improving predictions of human behavior).
The main goal of the collection is to present and illustrate, within a single volume, alternative strategies for conducting research in the domain of decision-making under risk and uncertainty and to clarify the advantages and disadvantages of each of them. And, in so doing, enable the interested reader to make informed assessments of what each program aims to achieve, has achieved or can achieve.
The focus of this collection are research programs, strategies and methods in decision science. Contributors are encouraged to address questions such as: which program has proved, or is likely to prove, most significant for producing results, in basic science or in applications; how do different methods compare in their treatment of a specific decision problem; the tradeoff between over-fitting and model simplicity; and more technical issues derived from the specific approaches compared.
Article-type may vary from philosophical or technical reviews of decision science to field or laboratory research results that illustrate an advocated program or method or compare different methods.