By Longbing Cao (auth.), Longbing Cao (eds.)
Data Mining and Multi-agent Integration offers state-of-the-art study, purposes and options in info mining, and the sensible use of cutting edge info applied sciences written by means of prime foreign researchers within the box. subject matters tested include:
- Integration of multiagent purposes and information mining
- Mining temporal styles to enhance brokers behavior
- Information enrichment via suggestion sharing
- Automatic net facts extraction in line with genetic algorithms and general expressions
- A multiagent studying paradigm for clinical info mining diagnostic workbench
- A multiagent facts mining framework
- Streaming info in complicated doubtful environments
- Large facts clustering
- A multiagent, multi-objective clustering algorithm
- Interactive internet setting for psychometric diagnostics
- Anomalies detection on dispensed firewalls utilizing info mining techniques
- Automated reasoning for dispensed and a number of resource of data
- Video contents identification
Data Mining and Multi-agent Integration is meant for college students, researchers, engineers and practitioners within the box, attracted to the synergy among brokers and knowledge mining. This ebook can also be suitable for readers in similar parts comparable to computing device studying, synthetic intelligence, clever platforms, wisdom engineering, human-computer interplay, clever info processing, determination aid structures, wisdom administration, organizational computing, social computing, complicated platforms, and smooth computing.
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Extra info for Data Mining and Multi-agent Integration
The core objectives of Agent Academy are to: • - Provide an easy-to-use tool for building agents, multi-agent systems and agent communities. • - Exploit Data Mining techniques for dynamically improving the behavior of agents and the decision-making process in multi-agent systems. • - Serve as a benchmark for the systematic study of agent intelligence generated by training them on available information and retraining them whenever needed. • - Empower enterprise agent solutions by improving the quality of provided services.
A typical example of Case 2 knowledge diffusion involves the improvement of the efficiency of agents participating in e-auctions. The goal here is to create both rational and efficient agent behaviors, which, in turn, will enable reliable agentmediated transactions. Another example is a web navigation engine, which tracks user actions in corporate sites and suggests possibly interesting sites. This framework can be extended to cover a large variety of web services and/or intranet applications. Finally, Case 3 encompasses solutions for ecosystem modeling and for web crawling with clusters of synergetic crawler agents.
In fact, the studies can also activate the possible emergence of agent-mining symbionts. For instance, the modeling and representation of domain knowledge and knowledge management in agents and data mining may be shared. It may serve as an intrinsic working mechanism for an agent-mining symbiont that has the capability of involving domain knowledge in agent-human interaction and data mining algorithm modeling, and managing knowledge for data mining agents and agent-based systems. To facilitate the studies of common enhancement issues, the possible methodologies and approaches needed may be highly diversified and cross-disciplinary.
Data Mining and Multi-agent Integration by Longbing Cao (auth.), Longbing Cao (eds.)