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CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
MIRAI: Multi-hierarchical, FS-Tree Based Music Information Retrieval System
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
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IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
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Journal of Intelligent and Robotic Systems
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MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
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In this paper, an agent is defined as a triple (S ,R S ,L S ), where S is a multi-hierarchical decision system, R S is a set of rules extracted from S defining values of its decision attributes, and L S is a language which the agent can use to communicate with other agents. L S is built from values of decision attributes in S which are treated as agent's external attributes. Classification attributes in S are treated as agent's internal attributes which for all agents are the same. If objects stored in two decision systems representing different agents are the same, then their descriptions in terms of internal attributes are the same as well. Agents can learn from each other definitions of their external attributes. If these definitions differ or are contradictory then agents may try to propose a new definition which is more acceptable to both of them. Standard semantics and agent centered semantics are introduced and used to describe the strategy of reaching consensus among agents. Expressions in the language L S are called analytical questions. Music information retrieval is taken as an application domain.