By Yusaku Shibata (auth.), Martti Mäntylä, Susan Finger, Tetsuo Tomiyama (eds.)
Computer Aided layout (CAD) know-how performs a key position in modern-day complex production surroundings. to minimize the time to marketplace, in achieving 0 illness caliber the 1st time, and use on hand construction and logistics assets successfully, product and layout approach wisdom protecting the complete product life-cycle has to be used all through product layout. as soon as generated, this in depth layout wisdom may be made on hand to later life-cycle actions. because of the expanding problem approximately international environmental matters and swiftly altering reasonably-priced scenario around the world, layout needs to convey excessive functionality not just in caliber and productiveness, but additionally in life-cycle matters, together with prolonged producer's legal responsibility. those pursuits require designers and engineers to exploit different types of layout wisdom intensively in the course of product layout and to generate layout details to be used in later phases of the product life-cycle akin to construction, distribution, operation, upkeep, reclamation, and recycling. accordingly, destiny CAD platforms needs to contain product and layout procedure wisdom, which aren't explicitly handled within the present platforms, of their layout instruments and layout item models.
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Additional resources for Knowledge Intensive CAD: Proceedings of the IFIP TC5 WG5.2 International Conference on Knowledge Intensive CAD, 16–18 September 1996, Pittsburgh, PA, USA
IJCAI-95 Workshop on Adaptation and Learning in Multiagent Systems, Montreal, Canada. Gruber, T. (1993) A Translation Approach to Portable Ontology Specification. Knowledge Acquisition, 5(2), 199--220. Iffenecker, C. (1994) Modelisation et reutilisation d'expertises variees en Conception. In Actes du Seminaire Interdisciplinaire "Memoire Collective", Compiegne, France. M. and Laresgoiti, I. (1995) Developing Industrial Multi-Agent Systems. In Proceedings of First International Conference on Multi-Agent Systems, San Francisco, USA, The AAAI press I The MIT Press.
If so, it does not send the REQUEST message over again, but gets the results directly from its task model. 5 A scenario - a small example As a design example, we considered a small mechanical system: a simple gear box, already described in details in (Shen and Barthes 1995a). 4. In the current implementation, only three types of messages (REQUEST, INFORM and NOTICE) are used. This paragraph shows how an agent handles such messages (see Figure 3). When an agent receives a REQUEST message for some sub-task, this agent chooses a method according its internal KB (knowledge about itself), executes this method for completing the sub-task, and then sends the results by an INFORM message to the sender (agent) of the Exchanging engineering design knowledge by cognitive agents 29 REQUEST message.
Each agent can reach any other active agent by means of a broadcasting message. All agents receive messages. They mayor may not understand such messages. When they do not understand a message, they simply do nothing. Whenever they understand the message, then they start working on it, provided the priority of the message is higher than the current work they were doing. Thus, agents are multi-threaded. When a new agent is introduced, it is simply connected to the network. Thereafter, it receives messages like any other agents.