, case-based reasoning, categorization and concept representation, emotions in agents, evaluation of intelligent systems, imprecise probabilities in AI, integrated intelligent systems, knowledge management, machine learning, neural networks, the semantic web, spatiotemporal reasoning, and uncertain reasoning....
The ability to acknowledge the inevitable uncertainty in their knowledge and reasoning is a prerequisite for AI systems to be truly truthful and reliable. In this paper, we present a taxonomy of uncertainty specific to vision-language AI systems, distinguishing between epistemic uncertainty (arising fr...
Uncertain and approximate knowledge representation to reasoning on classification with a fuzzy networks based system. Fuzzy Systems Conference Proceedings, FUZZ- IEEE'99. 3, pp. 1632-1637, 1999.M.N.Omri,and T.Chenaina.Uncertain and Approximate Knowledge Representation to Reasoning on Classification ...
Because human knowledge is uncertain, knowledgebase systems must include an uncertainty scheme. Many procedures have been developed to handle uncertain reasoning in expert systems. It is therefore important to investigate the appropriateness of the available techniques before applying one to a specific pro...
and information analysis in the Orient phase is heavily influenced by the existing (background) knowledge and understanding of the current situations at various levels including social, political, economic, cultural, administrative, logistic capabilities, resource availability, past experiences, and so on...
For a given subject entity es and query relation rq, the uncertain knowledge graph reasoning task is to predict the possible object entity eo, and deduce Methodology We perform UKGR tasks in two steps: multi-hop reasoning and causal effects estimating. Firstly, we propose a pathfinding agent and...
* Non-monotonic reasoning * Conditional Logics * Argumentation theory * Belief change and merging * Similarity-based reasoning * Ontologies and description logics * Construction of models from elicitation, data mining and knowledge discovery * Uncertain reasoning in information retrieval, filtering, fusio...
International Conference on Rough Sets and Knowledge Technology Abstract Uncertainty is one basic feature in the information processing, and the expressing and processing of uncertain information have attracted more attentions. There are many theories introduced to process the uncertain information, such as...
For decades, Bayesian networks [1] have played a leading role in plausible reasoning and knowledge representation in the AI community [2]. Other formalisms were also used to enable reasoning under uncertainty, such as fuzzy conceptual graphs, influence diagrams, Markov models, neural networks, and...
Information fusion technique like evidence theory has been widely applied in the data classification to improve the performance of classifier. A new fuzzy-belief K-nearest neighbor (FBK-NN) classifier is proposed based on evidential reasoning for dealing with uncertain data. In FBK-NN, each labeled...