Titlebook: Cooperative Information Agents; First International Peter Kandzia,Matthias Klusch Conference proceedings 1997 Springer-Verlag Berlin Heide

Volatile-Oils

Knowledge rovers: Cooperative intelligent agent support for enterprise information architectures,re discussed for each layer, access scenarios are presented, and the role of knowledge rovers is discussed. Knowledge rovers represent a . of cooperating intelligent agents that may be configured to support enterprise tasks, scenarios, and decision-makers. These rovers play specific roles within an

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Psa617

Enriching active databases with agent technology,nce. They are a promising paradigm to serve as a foundation for future computing environments in general, and information systems in particular. At the same time database research has seen the rise of active databases, database systems that add autonomous behaviour to a database. In this paper, we i

輕而薄

Result sharing among agents using reactive rules,te how ECA (Event-Condition-Action) rules can be used for supporting result shared cooperation. Further, we demonstrate how composite events as defined within active databases can help a problem solving agent to precisely specify when to take responsive action to multiple result notifications.

white-matter

Metadatabase meets distributed AI,gration is to build interfaces between the different databases being integrated. This approach holds, for a particular case, at a specific point in time. In this case however, the database structures need to be adapted. Such adaptation is not advisable since the local systems are usually important f

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saturated-fat

Neural fuzzy agents for database search,e user‘s likes and dislikes. A neural system uses training data to form and tune the rules. The profile is a preference map or a bumpy utility surface over the space of search objects. Rules define fuzzy patches that cover the bumps as learning unfolds and as the fuzzy agent system gives a finer app

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