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A NEW AGENT MATCHING SCHEME USING AN ORDERED FUZZY SIMILARITY MEASURE AND GAME THEORY
Author(s) -
Kebriaei Hamed,
Majd Vahid Johari,
RahimiKian Ashkan
Publication year - 2008
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.2008.00324.x
Subject(s) - matching (statistics) , fuzzy logic , computer science , stackelberg competition , similarity (geometry) , similarity measure , tree (set theory) , measure (data warehouse) , representation (politics) , game theory , artificial intelligence , mathematics , theoretical computer science , data mining , mathematical economics , image (mathematics) , politics , political science , law , mathematical analysis , statistics
In this paper, an agent matching method for bilateral contracts in a multi‐agent market is proposed. Each agent has a hierarchical representation of its trading commodity attributes by a tree structure of fuzzy attributes. Using this structure, the similarity between the trees of each pair of buyer and seller is computed using a new ordered fuzzy similarity algorithm. Then, using the concept of Stackelberg equilibrium in a leader–follower game, matchmaking is performed among the sellers and buyers. The fuzzy similarities of each agent with others in its personal viewpoint have been used as its payoffs in a bimatrix game. Through a case study for bilateral contracts of energy, the capabilities of the proposed agent‐based system are illustrated.