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A Performative-Based Information Capacity Calculation Metric for MultiAgent Interaction Protocols

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Advances in Artificial Intelligence and Soft Computing (MICAI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9413))

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Abstract

A performative-based information capacity calculation metric for MultiAgent Interaction Protocols is developed. The metric uses Shannon’s L-channel combinatorial information capacity calculation idea. In the approach, MultiAgent System (MAS) protocol is modeled as a discrete noiseless channel and provides not data level but language specific information capacity calculation for high level performative-based protocols. The amount of information that flow in MAS due to FIPA-ACL performatives used in given communication protocol is measured and figured out. The unit of measurement is bits per performative. Since the metric is a design time metric, it gives the system designer an opportunity to evaluate his/her design without implementing and testing it. In the application of the proposed metric to FIPA contract net protocol and its iterated versions, we observed a correlation between iteration counts and metric values.

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Author information

Authors and Affiliations

  1. Business Intelligence and Datawarehouse Systems Department, Akbank T.A.S, Istanbul, Turkey

    Dogus Bebek

  2. Computer Engineering Department, Engineering and Architecture Faculty, Gediz University, Menemen, Izmir, Turkey

    Hurevren Kilic

Authors
  1. Dogus Bebek
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  2. Hurevren Kilic
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Corresponding author

Correspondence to Hurevren Kilic .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico

    Grigori Sidorov

  2. Facultad de ciencias, Universidad AutĂłnoma Nacional, MĂ©xico, Distrito Federal, Mexico

    SofĂ­a N. Galicia-Haro

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Bebek, D., Kilic, H. (2015). A Performative-Based Information Capacity Calculation Metric for MultiAgent Interaction Protocols. In: Sidorov, G., Galicia-Haro, S. (eds) Advances in Artificial Intelligence and Soft Computing. MICAI 2015. Lecture Notes in Computer Science(), vol 9413. Springer, Cham. https://doi.org/10.1007/978-3-319-27060-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-27060-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27059-3

  • Online ISBN: 978-3-319-27060-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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