The INLA package provides a tool for computationally efficient Bayesian modeling and inference various widely used models, more formally the class of latent Gaussian models. It is non-sampling based framework which approximate results inference, using sparse matrices. swift uptake this rooted in computational efficiency approach catalyzed by demand presented big data era. In paper, we present n...

Hallucinations, a cardinal feature of psychotic disorders such as schizophrenia, are known to depend on excessive striatal dopamine. However, an underlying cognitive mechanism linking dopamine dysregulation and the experience of hallucinatory percepts remains elusive. Bayesian models explain perception as an optimal combination of prior expectations and new sensory evidence, where perceptual di...

The evaluation of user modeling systems is an important though often neglected area. Evaluating the inference of user properties can help to identify failures in the user model. In this paper we propose two methods to assess the accuracy of the user model. The assumptions about the user might either be compared to an external test, or might be used to predict the users’ behavior. Two studies wi...

This paper presents a new interval type-2 fuzzy inference system to handle uncertainty using reduced-set vector learning mechanism based on hybrid kernels. Firstly, a novel concept, interval kernel, is proposed. It establishes a relationship between interval type-2 fuzzy membership and hybrid kernel. According to it, a particular interval type-2 fuzzy inference system is built, which abandons t...

This paper presents an approach to similarity based approximate reasoning that elucidates the connection between similarity and existing approaches to inference in approximate reasoning methodology. A set of axioms is proposed to compute a reasonable measure of similarity between two fuzzy sets. Such a measure of similarity is then used at different stages to derive a conclusion in approximate ...

Given a growing sequence of observations x1,...,xn,... , one is required, at each time step n, to make some inference about the stochastic mechanism generating the sequence. Several problems that have numerous applications in different branches of mathematics and computer science can be formulated in this way. For example, one may want to forecast probabilities of the next outcome xn+1 (sequenc...

Plan Recognition algorithms require to recognize a complete hierarchy explaining the agent’s actions and goals. While the output of such algorithms is informative to the recognizer, the cost of its calculation is high in run-time, space, and completeness. Moreover, performing plan recognition online requires the observing agent to reason about future actions that have not yet been seen and main...

The research in AI is divided in to two categories Knowledge representation and general. For making the computer or Machine as intelligent as human being we require two things Knowledge representation and inference mechanism. Development of an AI system is a crucial task because some time we have incomplete information and it can be ambiguous and uncertain. So solution to these problems is to b...

a r t i c l e i n f o In many mining, civil, and petroleum engineering applications diamond bit drilling is widely used due to high penetration rate, core recovery and its ability to drill with less deviation. Recently, many research have been conducted to estimate the penetration rate of diamond drilling which can be considered as one of the most important parameters in project planning and co...