A vector equilibrium problem is generally defined by a bifunction which takes values in a partially ordered vector space. In particular, when this space is endowed with a componentwise ordering, the vector equilibrium problem can be decomposed into a family of equilibrium subproblems, each of them being governed by a bifunction obtained from the initial one by selecting some of its scalar compo...

Different kind of methodologies have been presented in the last decades and achieved broad applications in structural damage detection (SDD). Particle swarm optimization (PSO) based algorithms have been confirmed to be effective for SDD. The method avoids inversion computation which is prone to be ill-posed or ill-conditioning. However, the accuracy of optimization algorithm is affected by its ...

We argue that the function of vision is to get correct and useful answers about the state of the world. However, given the state of the world is not uniquely specified by the visual input, the visual system must make inferences. Thus, theories of visual perception will be theories of inference, and we need a language in which theories of inference can be described. Analogous to calculus being a...

This paper deals with Decision-Making in the context of multiattribute utility theory and, more precisely, with the problem of efficiently determining the best alternative w.r.t. an agent’s preferences (choice problem). We assume that alternatives are elements of a product set of attributes and that the agent’s preferences are represented by a generalized additive decomposable (GAI) utility on ...

This paper deals with Decision-Making in the context of multiattribute utility theory and, more precisely, with the problem of efficiently determining the best alternative w.r.t. an agent’s preferences (choice problem). We assume that alternatives are elements of a product set of attributes and that the agent’s preferences are represented by a generalized additive decomposable (GAI) utility on ...

Objective Bayesian probability is often defined over rather simple domains, e.g., finite event spaces or propositional languages. This paper investigates the extension of objective Bayesianism to first-order logical languages. It is argued that the objective Bayesian should choose a probability function, from all those that satisfy constraints imposed by background knowledge, that is closest to...

The function of vision is to get correct and useful answers about the state of the world. However, given that the state of the world is not uniquely specified by the visual input, the visual system must make good guesses or inferences. Thus, theories of visual system functions will be theories of inference, and we need a language in which theories of inference can be described. Analogous to cal...

Probabilistic independence can dramatically simplify the task of eliciting, representing, and computing with probabilities in large domains. A key technique in achieving these benefits is the idea of graphical modeling. We survey existing notions of independence for utility functions in a multi-attribute space, and suggest that these can be used to achieve similar advantages. Our new results co...