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Towards Distributed Reasoning for Behavioral Optimization

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Part of the IFIP International Federation for Information Processing book series (IFIPAICT,volume 216)

Abstract

We propose an architecture which supports the behavioral self-optimization of complex systems. In this architecture we bring together specification-based reasoning and the framework of ant colony optimization (ACO). By this we provide a foundation for distributed reasoning about different properties of the solution space represented by different viewpoint specifications. As a side-effect of reasoning we propagate the information about promising areas in the solution space to the current state. Consequently the system’s decisions can be improved by considering the long term values of certain behavioral trajectories (given a certain situational horizon). We consider this feature to be a contribution to autonomic computing.

Keywords

  • Solution Space
  • Description Logic
  • Fuzzy Concept
  • Tree Automaton
  • Membrane Computing

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2006 International Federation for Information Processing

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Cebulla, M. (2006). Towards Distributed Reasoning for Behavioral Optimization. In: Pan, Y., Rammig, F.J., Schmeck, H., Solar, M. (eds) Biologically Inspired Cooperative Computing. BICC 2006. IFIP International Federation for Information Processing, vol 216. Springer, Boston, MA . https://doi.org/10.1007/978-0-387-34733-2_7

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  • DOI: https://doi.org/10.1007/978-0-387-34733-2_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-34632-8

  • Online ISBN: 978-0-387-34733-2

  • eBook Packages: Computer ScienceComputer Science (R0)