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... A multi-agent system (e. ...
In previous multi-agent systems, weighted keywords/keyphrases were put forward to represent the information an agent is carrying or seeking. ... , 1995], and the Resource Description Framework (RDF) [Lassila and Swick, 1999], node-labelled, arc-labelled, and arc-weighted trees are employed for the knowledge representation.
For the uniform representation and exchange of product/service trees, a weighted extension of Object-Oriented RuleML [Boley 2003] could be used to serialize the tree. ...
Based on the above tree representation, a technique needs to be developed and implemented for the tree similarity measure. This technique can be extended by clustering methods to realize the match-maker of a multi-agent system, which pairs sufficiently similar agents. Such techniques could also be used in other applications, such as e-Learning and e-Health. ... Background
In multi-agent systems, agents can carry various message contents (e. ... In previous multi-agent systems, weighted keywords/keyphrases were proposed to represent the message. However, in order to flexibly represent complex structures and allow more fine-grained interaction between agents, a special tree representation is proposed in this thesis. More precisely, in this thesis, trees are node-labelled, arc-labelled, and arc-weighted. ... In the virtual marketplace provided by a multi-agent system, the most common activity for buyer and seller agents is negotiation. ... Since offer and request contents are represented as node-labelled, arc-labelled, and arc-weighted trees, a technique that could compute the similarity of this kind of trees is necessary.
The study of the tree similarity (or tree distance) techniques is not a new topic. ... Generally, those techniques use three operations [Lu 1979], insertion, deletion, and modification, for transforming one tree to another tree, computing how many operations the transformation needs, and thus indirectly getting the similarity of two trees.
Approximate Word count = 1490
Approximate Pages = 6
(250 words per page double spaced)
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