The testing and formal verification of black box software components is a challenging domain. The problem is even harder when specifications of these components are not available. An approach to cope with this problem is to combine testing with learning techniques, such that the learned models of the components can be used to explore unknown implementation and thus facilitate testing efforts. I...

Available approaches for Association Rule Mining (ARM) generates a large number of association rules, these rules may be trivial and redundant and also such rules are difficult to manage and understand for the users. If we consider their complexity, then it consumes lots of time and memory. Sometimes decision making is impossible for such kinds of association rules. An inference approach is req...

The main condition of the differently implicational inferencealgorithm is reconsidered from a contrary direction, which motivatesa new fuzzy inference strategy, called the double fuzzyimplications-based restriction inference algorithm. New restrictioninference principle is proposed, which improves the principle of thefull implication restriction inference algorithm. Furthermore,focusing on the ...

If one has attributed certain initial beliefs to an agent, it is sometimes possible to reason about further beliefs the agent must hold by observing what conclusions one’s own reasoning mechanism draws when given the initial beliefs as premises. This technique is called simulative inference. In an earlier paper, we described a logic of belief in which the reasoning that generates beliefs is mod...

In order to handle real-world problems, state-of-the-art probabilistic logic and learning frameworks, such as ProbLog, reduce the expensive inference to an efficient Weighted Model Counting. To do so ProbLog employs a sequence of transformation steps, called an inference pipeline. Each step in the probabilistic inference pipeline is called a pipeline component. The choice of the mechanism to im...

In this study, the fuzzy causal map inference mechanisms are analyzed for decision making tasks and a comparative analysis is performed to handle with the uncertainty in the problem of pulmonary risk prediction. Fuzzy Cognitive Mapping (FCM) is a causal graphical representation including nodes, determining the most relevant factors of a complex system, and links between these nodes determining ...

Molecular computing is a new paradigm to perform calculations using nanotechnology. This paper presents the overall research direction from which molecular inference and expert systems are emerging. It introduces the subject matter and a general description of the problems involved. This includes selected methods of knowledge representation by DNA oligonucleotides, strategies of the inference m...

In many applications we are interested in making inference on latent time series from indirect measurements, which are often low-dimensional projections resulting from mixing or aggregation. Positron emission tomography, super-resolution, and network traffic monitoring are some examples. Inference in such settings requires solving a sequence of ill-posed inverse problems, yt = Axt , where the p...

Artificial Intelligence systems cannot yet match human abilities to apply knowledge situations that vary from what they have been programmed for, or trained for. In visual object recognition, methods of inference exploiting top-down information (from a model) shown be effective for recognising entities in difficult conditions. Here component this type inference, called ‘projection’, is key mech...

Abstract With the development and improvement of deep learning technology, its application practice in modal data (image, speech, text) has been achieved tremendously. In this paper, based on neural network modality class model learning, we analyze adaptation to visual question answer system, propose a gated attention mechanism, construct question, prediction mechanism adapted recurrent transfe...