Fuzzy Unification and Argumentation for Well-Founded Semantics

  • Ralf Schweimeier
  • Michael Schroeder
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2932)


Argumentation as metaphor for logic programming semantics is a sound basis to define negotiating agents. If such agents operate in an open system, they have to be able to negotiate and argue efficiently in a goal-directed fashion and they have to deal with uncertain and vague knowledge. In this paper, we define an argumentation framework with fuzzy unification and reasoning for the well-founded semantics to handle uncertainty. In particular, we address three main problems: how to define a goal-directed top-down proof procedure for justified arguments, which is important for agents which have to respond in real-time; how to provide expressive knowledge representation including default and explicit negation and uncertainty, which is among others part of agent communication languages such as FIPA or KQML; how to deal with reasoning in open agent systems, where agents should be able to reason despite misunderstandings.

To deal with these problems, we introduce a basic argumentation framework and extend it to cope with fuzzy reasoning and fuzzy unification. For the latter case, we develop a corresponding sound and complete top-down proof procedure.


Logic Program Logic Programming Edit Distance Fuzzy Reasoning Argumentation Framework 
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 2004

Authors and Affiliations

  • Ralf Schweimeier
    • 1
  • Michael Schroeder
    • 1
    • 2
  1. 1.Department of ComputingCity UniversityLondonUK
  2. 2.Department of Computer ScienceTechnische Universität DresdenDresdenGermany

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