Titlebook: Autonomous Intelligent Systems: Multi-Agents and Data Mining; Second International Vladimir Gorodetsky,Chengqi Zhang,Longbing Cao Conferenc

漂泊

Semantic Modelling in Agent-Based Software Developmentfunctionality extensions into existing multi-agent software systems, we present our semantic modelling approach. It defines a structured annotation process, proposing concepts, techniques and a methodical support for the formal description of static and dynamic semantic information of software agent

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四溢

Intelligent Agents for Real Time Data Mining in Telecommunications Networkse showed their advantages on helping to manage this information and transforming it in useful knowledge. However, due to the dynamics of the environment of Telecommunications Networks, the simple application or adaptation of DM techniques is not enough to obtain timely a deeper knowledge. In this pa

jungle

Architecture of Typical Sensor Agent for Learning and Classification Networke important requirements to any distributed learning and decision making systems. In many such applications, input data arrive from spatially distributed sensors structured in sensor networks. An increasing interest to what is called .for which agent-based technology seems to be rather attractive im

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Self-organizing Multi-agent Systems for Data Miningented. The key idea behind the framework is to provide agents with deployment policies for their deployment and coordinations as relations between them and other agents. As a result, a federation of distributed agents can migrate and coordinate over a distributed system in a self-organizing manner.

流利圆滑

Role-Based Decision Mining for Multiagent Emergency Response Managements for situation management, selection of a right decision maker and supplying him/her necessary data. During decision making support a large amount of raw data describing current situation, users preferences, found solutions and final decisions done by decision maker are accumulated in the repositor

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