Representation Of Judgment Research Articles

Urteil und Komödie in der italienischen Renaissance und in Giordano Brunos Candelaio

The essay examines the practice of judgement in Giordano Bruno’s comedy Candelaio. The comic effect of the piece is largely due to the asymmetry between those with poor judgment and those who are intellectually superior to them. Bruno addresses the importance of an untroubled power of judgement both in the prologue and in various passages of the text. The characters’ practice of judgement thus constitutes the plot of Candelaio and is at the same time explicitly thematized throughout the text. The essay shows that the representation of judgment in Candelaio is intertextually connected with the history of comedy in the Cinquecento. Comedy writers such as Bibbiena and Machiavelli already discovered the practice of judgement as a source of laughter. Bruno follows their models but complicates the plot and deepens the reflection on judgment by drawing on ideas from his work De umbris idearum, in which he lays the foundations of his epistemology. In Candelaio, however, Bruno is not interested in spreading philosophical views. It is rather a question of mocking social conventions, the contingency of which is uncovered.

When Is a Model Good Enough? Deriving the Expected Value of Model Improvement via Specifying Internal Model Discrepancies

A “law-driven” or “mechanistic” computer model is a representation of judgments about the functional relationship between one set of quantities (the model inputs) and another set of target quantities (the model outputs). We recognize that we can rarely define with certainty a “true” model for a particular problem. Building an “incorrect” model will result in an uncertain prediction error, which we denote “structural uncertainty.” Structural uncertainty can be quantified within a Bayesian framework via the specification of a series of internal discrepancy terms, each representing at a subfunction level within the model the difference between the subfunction output and the true value of the intermediate parameter implied by the subfunction. By using value of information analysis we can then determine the expected value of learning the discrepancy terms, which we loosely interpret as an upper bound on the “expected value of model improvement.” We illustrate the method using a case study model drawn from the health economics literature.

Decisions, Structure, and Natural Law

The object here is to show that our thinking processes and our physical forms and those of all things that exist, are a result of response in nature to influences as stimuli, brought about by natural occurrences. The ideas are developed through a generalization of the role judgment plays in decision making. Judgment serves as the basic link between our conscious awareness and the stimuli of the natural world. The mathematics used to represent natural laws is derived from stimulus-response theory and this in turn from the representation of judgment as it is used in decision-making. The representation of discrete judgment as a principal eigenvalue problem is generalized to the continuous case through Fredholm theory. Solving the resulting fundamental functional equation, which is a necessary condition for the existence of a solution, gives rise to damped periodic oscillation. The Fourier transform of the real valued solution has a perturbed inverse square representation that poses a question raised on occasion in science about the full accuracy of exact inverse square laws of gravitation, optics and of electric charges. The Fourier transform of the complex valued solution is a linear combination of Dirac type distribution of impulsive functions representing how the brain must operate to respond to external stimuli. A generalization is made to a functional equation in operator form with its solution. These solutions describe all forms that exist in nature as anything that responds to influences. These considerations that originate in the mathematics of judgment, serve as a unifying approach to our understanding and to creating tools for modeling and solving complex physical and behavioral problems. http://dx.doi.org/10.13033/ijahp.v1i1.13

A Lively Representation of Judgments

A Lively Representation of Judgments