Titlebook: Discrete Event Modeling and Simulation Technologies; A Tapestry of System Hessam S. Sarjoughian,Fran?ois E. Cellier Book 2001 Springer Scie

被告

https://doi.org/10.5822/978-1-61091-864-0e and autonomous nature of these computational mechanisms that lend themselves to real-world application. Although the early motivation for the development of artificial neural networks was inspired by biological neural networks, today’s artificial neural networks have little or nothing in common wi

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POWER

Neue Akzente der Suburbanisierungcting test beds for multi-agent systems is presented. The formalism is rooted in DEVS and describes agents and their environments as reflective time triggered automata. The hierarchical compositional model design is complemented by an abstract simulator to support the parallel, discrete event execut

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Klaus Brake,Jens S. Dangschat,Günter Herfert This paper presents a formal methodology to translate knowledge so that the plans produced in one planner can be utilized and learned from in another. The methodology presented allows entire plans consisting of predicates, actions and the orderings between them to be converted from one representati

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https://doi.org/10.1007/978-1-4757-3554-3agent-based model; agent-based modeling; artificial intelligence; development; intelligence; learning; mod

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Why Engineering Models Do Not Have a Frame Problem,issues so that engineers can understand why the frame problem is not contrived, but it also points out to AI scientists that as they search for efficient ways to deal with the frame problem, their solutions begin to look suspiciously like what the more sophisticated engineers have been doing.