Uncertain logic is a generalization of classical logic for dealing with uncertain knowledge via uncertainty theory. The truth value is defined as the uncertain measure that a proposition is true. In this paper, a numerical method for calculating the truth value of uncertain formulas is proposed and some examples are presented. 2011 Elsevier Ltd. All rights reserved.

Legitimate expectation in the context of culpa in contrahendo is an important legal concept for the study of good faith and the duty to negotiate with good care. However when wanting to model it and reason about it, one finds that most existing legal formalisations do not directly account for the concept. In this paper we present a formal model that can explicitly model and reason about legitim...

An earlier study (3) showed that simple reaction time (RT) varies 'with S's uncertainty about time of stimulus occurrence. This time uncertainty is a function of both the mean duration of the time (foreperiod) between a warning signal and the stimulus and the variability within the series of foreperiods. Foreperiod variability adds uncertainty directly and mean foreperiod is important since S's...

In this paper, we propose an uncertainty-aware learning from demonstration method by presenting a novel uncertainty estimation method utilizing a mixture density network appropriate for modeling complex and noisy human behaviors. The proposed uncertainty acquisition can be done with a single forward path without Monte Carlo sampling and is suitable for real-time robotics applications. The prope...

We present a proximal algorithm that performs variational recursion on the space of joint probability measures to propagate stochastic uncertainties in power system dynamics over high dimensional state space. The proposed takes advantage exact nonlinearity structures trajectory-level networked systems, and is nonparametric. Lifting allows us design scalable obviates gridding underlying which co...

This paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual bootstrapping, which are referred to, in a general term, as ‘collaborative bootstrapping’. The paper indicates that uncertainty reduction is an important factor for enhancing the performance of collaborative bootstrapping. It proposes a new measure for representing the degree of un...

this paper assumes the cell formation problem as a distributed decision network. it proposes an approach based on application and extension of information theory concepts, in order to analyze informational complexity in an agent- based system, due to interdependence between agents. based on this approach, new quantitative concepts and definitions are proposed in order to measure the amount of t...

Indeterminacy associated with probing of a quantum state is commonly expressed through spectral distances (metric) featured in the outcomes repeated experiments. Here we express it as an effective amount (measure) distinct instead. The resulting $\mu$-uncertainties are described by number theory [1] whose central result, existence minimal amount, leads to well-defined notion intrinsic irremovab...