4sr is an extension of 4store where we are implementing backward chained reasoning. Currently a subset of RDFS is supported. This set includes: rdfs:subClassOf, rdfs:subPropertyOf, rdfs:domain and rdfs:range.
development of self-healing systems capable of making inferences about their own behavior, such as diagnosing faults and performance degradations. uses a cost-efficient technique for adaptive diagnosis that combines probabilistic inference with online, active selection of the most-informative measurements called probes. Probes are end-to-end test transactions that collect information about the availability and performance of a distributed system. Given the probe results (symptoms), RAIL performs Bayesian inference in order to find the most likely explanation (cause), An important difference between RAIL's approach and ''passive'' data analysis is in RAIL's ability to select and execute probes online. This approach, called active probing, uses an information-theoretic criterion called information gain in order to select adaptively only a small set of the most informative probes at any given time; this approach significantly reduces the overall number of probes required
Bayesian inference is one of two dominant approaches to statistical inference. The word Bayesian refers to the influence of Reverend Thomas Bayes. Bayesian inference is a modern revival of the classical definition of probability.
Multiple channels and types of events…
… executing in multiple Inference Agents (Event Processing Agents on an Event Processing Network)…
… where Events drive Production Rules with associated (shared) data…
… and event patterns (complex events) are derived from the simple events and also drive Production Rules via inferencing…
… to lead to “real-time” decisions.