with conventional expert systems, it is clear that 1) 2) 3) AARS can reduce the size of the rule base; AARS uses linguistic variables rather than quantitative variables; AARS increases the system's flexibility. In future research, we expect to 1) associate observation P,' and rule R , with certainty factors CF, and CF, and derive a certainty factor for consequent experiment with other forms of ...

Geospacial Reasoning’ is spacial reasoning including geographic data. This is an extremely board area. In this deliverable we presented our approaches to cover enough aspects from this area such that it is useful for Semantic Web applications. An important building block is a hierarchy of graphs which combines very low level coordinate based computations with abstract symbolic reasoning. Anothe...

Many health and safety problems, including war and terrorism, are by-products of how people reason about risk. I describe a new approach to reasoning about risk that implements a modern dual-process model of memory called fuzzytrace theory. This approach posits encoding of both verbatim and gist representations, with reliance on the latter whenever possible; dependence of reasoning on retrieval...

We consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account. Furthermore, these systems take also fuzzy uncertainty into account by their fuzzy partitioning of input and ...

We formalize reasoning about fuzzy belief and fuzzy common belief, especially incomparable beliefs, in multi-agent systems by using a logical system based on Fitting’s many-valued modal logic, where incomparable beliefs mean beliefs whose degrees are not totally ordered. Completeness and decidability results for the logic of fuzzy belief and common belief are established while implicitly exploi...

Fuzzy Answer Set Programming (FASP) combines the nonmonotonic reasoning typical of Answer Set Programming with the capability of Fuzzy Logic to deal with imprecise information and paraconsistent reasoning. In the context of paraconsistent reasoning, the fundamental principle of minimal undefinedness states that truth degrees close to 0 and 1 should be preferred to those close to 0.5, to minimiz...

In the approximate fuzzy reasoning the covering over of fuzzy rule base input and rule premise of a rule determines the importance of that fuzzy rule and the rule output as well. An axiom system has been created, describing the relationship between the fuzzy rule base system, rule input and rule output. By using distance-based operators a novel reasoning method appears by the compositional rule...

Product development process can be viewed as a set of sub-processes with stronger interrelated dependency relationships. In this article, the quantitative and qualitative dependency measures of serial and parallel product development processes are analyzed. The neural-network-driven fuzzy reasoning mechanism of dependency relationships is developed in the case that there is no sufficient quanti...