Reducing Negative Complexity by a Computational Semiotic System

Reducing Negative Complexity by a Computational Semiotic System

Gerd Doben-Henisch (University of Applied Sciences-Frankfurt am Main, Germany)
Copyright: © 2007 |Pages: 13
DOI: 10.4018/978-1-59904-063-9.ch012


The chapter describes the set-up for an experiment in computational semiotics. Starting with a hypothesis about negative complexity in the environment of human persons today it describes a strategy, how to assist human persons to reduce this complexity by using a semiotic system. The basic ingredients of this strategy are a visual programming interface with an appropriate abstract state machine, which has to be realized by distributed virtual machines. The distributed virtual machines must be scalable, have to allow parallel processing, have to be fault tolerant, and should have the potential to work in real time. The objects, which have to be processed by these virtual machines, are logical models (LModels), which represent dynamic knowledge, including self learning systems. The descriptions are based on a concrete open source project called Planet Earth Simulator.

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