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Modeling Agents and Agent Systems

  • Theodor Lettmann
  • Michael Baumann
  • Markus Eberling
  • Thomas Kemmerich
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6910)

Abstract

In present agent definitions, we often find different names and definitions for similar concepts. Many works on multiagent systems use abstract and informal descriptions to introduce the topic. Even books on multiagent systems often lack a formal definition or use a self-contained formalism. Our goal is to present a universal and formal description for agent systems that can be used as a core model with other existing models as special cases. This core model allows clear specification of agent systems and their properties. Design decisions are made explicitly and, by that, become a mean of comparison for different approaches. The proposed definitions for single- and multiagent systems address all basic properties while leaving space for extensions and can thus be used to talk about concepts using a homogeneous notation. The comparisons of our definition to existing models show that the most-cited descriptions can be expressed with our formalism which shows that there is a basic consensus on fundamental properties of agent systems.

Keywords

Internal State Multiagent System Agent System Markov Decision Process Intelligent Agent 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Theodor Lettmann
    • 1
  • Michael Baumann
    • 2
  • Markus Eberling
    • 1
  • Thomas Kemmerich
    • 2
  1. 1.Department of Computer ScienceUniversity of PaderbornPaderbornGermany
  2. 2.International Graduate School of Dynamic Intelligent SystemsUniversity of PaderbornPaderbornGermany

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