The objective of this document(*)
is to provide some rational, structured access to an analysis of cognitive and agent architectures (for
more information on accessing the document, see the Reader's Guide). Twelve architectures have
been used for this preliminary analysis representing a wide range of
current architectures in artificial
intelligence (AI). The aim of the project is to facilitate both
an understanding of current architectures and provide insight to the
development of future, improved intelligent agent architectures.
This work was based on publications from 1992 and before and has not
been authorized by the researchers responsible for particular
architectures (see DISCLAIMER for additional
information).
On Event Processing Agents implies a “new” event processing reference architecture with terms like,
(1) simple event processing agents for filtering and routing,
(2) mediated event processing agents for event enrichment, transformation, validation,
(3) complex event processing agents for pattern detection, and
(4) intelligent event processing agents for prediction, decisions.
Frankly, while I generally agree with the concepts, I think the terms in On Event Processing Agents tend to add to the confusion because these concepts in On Event Processing Agents are following, almost exactly, the same reference architecture (and terms) for MSDF, illustrated again below to aid the reader.
ABLE is a Java framework, component library, and productivity tool kit for building intelligent agents using machine learning and reasoning. The ABLE research project is made available by the IBM T. J. Watson Research Center.
Business narrative is a set of techniques based on the collection and interpretation of stories collected from a workplace. This technique is most effective when applied to seemingly intractable problems such as culture change, trust, innovation, leadersh
Brand new... good for you! "To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic."
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.
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B. Savarimuthu, и S. Cranefield. Normative Multi-Agent Systems, 09121, Dagstuhl, Germany, Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany, (2009)
J. Günther, E. May, F. Münch, S. Löffler, S. Beck, и E. Hilgendorf. Leroux, Christophe; Labruto, Roberto (Hrsg.): Suggestion for a green paper on legal issues in robotics, euRobotics, The European Robotics Coordination Action., (2012)