A Similarity Evaluation Technique for Cooperative Problem Solving with a Group of Agents

  • Seppo Puuronen
  • Vagan Terziyan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1652)


Evaluation of distance or similarity is very important in cooperative problem solving with a group of agents. Distance between problems is used by agents to recognize nearest solved problems for a new problem, distance between solutions is necessary to compare and evaluate the solutions made by different agents, and distance between agents is useful to evaluate weights of the agents to be able to integrate them by weighted voting. The goal of this paper is to develop a similarity evaluation technique to be used for cooperative problem solving with a group of agents. Virtual training environment used for this goal is represented by predicates that define relationships within three sets: problems, solutions, and agents. We derive and interpret both internal and external relations between the pairs of subsets taken of the three sets: problems, solutions, and agents. The refinement technique presented is based on the derivation of the most supported solution of the group of agents and refining it further using a multilevel structure of agents.


Weighted Vote External Relation Multilevel Structure Total Support Cooperative Problem 
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 1999

Authors and Affiliations

  • Seppo Puuronen
    • 1
  • Vagan Terziyan
    • 2
  1. 1.Department of Computer Science and Information SystemsUniversity of JyväskyläJyväskyläFinland
  2. 2.Kharkov State Technical University of RadioelectronicsKharkovUkraine

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