One kind of deliberation involves an individual reassessing the strengths of her beliefs in the light of new evidence. Bayesian epistemology measures the strength to which one ought to believe a proposition by its probability relative to all available evidence, and thus provides a normative account of individual deliberation. This can be extended to an account of individual judgement by treatin...

As a compact representation of joint probability distributions over dependence graph random variables, and tool for modelling reasoning in the presence uncertainty, Bayesian networks are great importance artificial intelligence to combine domain knowledge, capture causal relationships, or learn from incomplete datasets. Known as NP-hard problem classical setting, inference pops up class algorit...

ABSTRACT: The problem of robust design is treated as a bi-objective optimization problem in which the performance mean and variation are optimized and minimized, respectively. A method for deriving a utility function as a local approximation of the efficient frontier is presented and investigated at different locations of candidate solutions, with different ranges of interest, and for efficient...

We construct a fully-fledged production economy model with Kahneman and Tversky’s Prospect Theory features. The agents’ objective function is a weighted sum of the usual utility over consumption and leisure and the utility over the relative changes of the agents’ wealth. It is also assumed that the agents are more sensitive to wealth losses than to gains. Apart from the changes in the utility, ...

In single-person decision theory, Bayesian rationality requires the agent first to attach subjective probabilities to each uncertain event, and then to maximize the expected value of a von Neumann–Morgenstern utility function (or NMUF) that is unique up to a cardinal equivalence class. When the agent receives new information, it also requires subjective probabilities to be revised according to ...

aim and background: deficit of theory of mind is a fundamental impairment of social skill in autistic children. the purpose of present study was evaluation of cognitive rehabilitation on social cognition abilities of children with high function autism. methods and materials: in present single subject study, 4 children with high function autism participated in study with no probably sampling. si...

Enabling trust to ensure more effective and efficient agent interaction is at the heart of the Semantic Web vision. We propose a computational trust model based on Bayesian decision theory in this paper. Our trust model combines a variety of sources of information to assist users with making correct decision in choosing the appropriate providers according to their preferences that expressed by ...

Decision making with adaptive utility provides a generalisation to classical Bayesian decision theory, allowing the creation of a normative theory for decision selection when preferences are initially uncertain. The theory of adaptive utility was introduced by Cyert & DeGroot [27], but had since received little attention or development. In particular, foundational issues had not been explored a...

We give a new approach in modeling the incomplete information in a buyer-seller game. We assume that the seller does not know the buyer's utility function at all. Usually the problem is solved by determining the Bayesian Nash equilibrium of the game, where it is assumed that the buyer's utility function has only some parameters unknown to the seller, and the seller knows the distribution of the...

According to objective Bayesianism, an agent’s degrees of belief should be determined by a probability function, out of all those that satisfy constraints imposed by background knowledge, that maximises entropy. A Bayesian net offers a way of efficiently representing a probability function and efficiently drawing inferences from that function. An objective Bayesian net is a Bayesian net represe...