In scenario optimization, decisions are made in the light of past situations (or scenarios), and the “risk” associated to a scenario decision refers to the possibility that the decision does not perform as expected in a new case at hand. In the presentation, we will discuss a deep, and universal, link that relates the risk to the “complexity” of the decision, where complexity is a concept associated to the amount of information by which the decision can be constructed. This theoretical result provides a support to the use of inductive methods in decision making problems.Non UBCUnreviewedAuthor affiliation: University of BresciaFacult
This paper examines empirically the impact of complexity on levels of participation and performance ...
Abstract. Decision Making is certainly the most important task of a manager and it is often a very d...
The scenario approach is a general methodology for data-based optimization that has attracted a grea...
In scenario optimization, decisions are made in the light of past situations (or scenarios), and the...
Scenario optimization is a broad scheme for data-driven decision-making in which experimental observ...
In previous contributions, it has been shown that the “complexity” is a key indicator to quantify th...
Scenario optimization considers decisions made on the grounds of past experience. A scenario decisio...
The scenario approach is a well-established methodology that allows one to generate solutions from a...
Undesirable rare and new events are hard to predict and their costs are hard to quantify. The scienc...
Scenarios are not (deterministic or probabilistic) predictions but explorations either of possible f...
This study complements the existing literature on decision-making processes and outcomes in complex ...
This investigation of risky decision making models the standard forced-choice two outcome lottery ta...
Although many Mathematical Programming techniques have been developed for application to decision ma...
We consider sequential decision problems where a first action is made prior to seeing any uncertaint...
This paper examines empirically the impact of complexity on levels of participation and performance ...
Abstract. Decision Making is certainly the most important task of a manager and it is often a very d...
The scenario approach is a general methodology for data-based optimization that has attracted a grea...
In scenario optimization, decisions are made in the light of past situations (or scenarios), and the...
Scenario optimization is a broad scheme for data-driven decision-making in which experimental observ...
In previous contributions, it has been shown that the “complexity” is a key indicator to quantify th...
Scenario optimization considers decisions made on the grounds of past experience. A scenario decisio...
The scenario approach is a well-established methodology that allows one to generate solutions from a...
Undesirable rare and new events are hard to predict and their costs are hard to quantify. The scienc...
Scenarios are not (deterministic or probabilistic) predictions but explorations either of possible f...
This study complements the existing literature on decision-making processes and outcomes in complex ...
This investigation of risky decision making models the standard forced-choice two outcome lottery ta...
Although many Mathematical Programming techniques have been developed for application to decision ma...
We consider sequential decision problems where a first action is made prior to seeing any uncertaint...
This paper examines empirically the impact of complexity on levels of participation and performance ...
Abstract. Decision Making is certainly the most important task of a manager and it is often a very d...
The scenario approach is a general methodology for data-based optimization that has attracted a grea...