Special Issue "Consensus and Intelligent Negotiation in Sensors Networks"
Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 13396
2. Air Institute, IoT Digital Innovation Hub, 37188 Salamanca, Spain
3. Department of Electronics, Information and Communication, Faculty of Engineering, Osaka Institute of Technology, Osaka 535-8585, Japan
Interests: artificial intelligence; smart cities; smart grids
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Interests: intelligent decision making; artificial intelligence; computational intelligence
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Consensus in group decision making involves discussion and deliberation among a group of sensors, with the aim of reaching an acceptable decision that reflects the opinion of every network member. Traditionally, the consensus reaching problem is modelled theoretically as a multi stage negotiation process. In a dynamic sensor network, the negotiation scenario changes with time. Many real-life problems require the development of dynamic consensus process models that represent the dynamic world effectively and realistically.
This Special Issue calls for innovative work that explores new frontiers and challenges in the fields of consensus reaching models for dynamic environments, intelligent negotiation processes, and AI algorithms that improve decision making in sensor networks. The works in this Special Issue may include new machine learning models, distributed AI proposals, group decision making, consensus processes, negotiation protocols, decision support systems, multi period decision making, adaptive consensus models, and so on, as well as case studies or reviews of the state-of-the-art, in all cases related to consensus or negotiation.
The topics of interest include, but are not limited to, the following:
- Distributed artificial intelligence models for sensor networks.
- Machine learning models for dynamic sensor networks.
- Group decision making for sensor networks.
- Decision support systems for sensor networks.
- Consensus processes for sensor networks.
- Multi period decision making for sensor networks.
- Adaptive consensus models for sensor networks.
- Clustering and classification algorithms for sensor networks.
- Deep and reinforcement learning for Sensor Networks.
- Fuzzy systems proposals for sensor networks control.
- Expert systems for sensor networks negotiation.
- Intelligent real time algorithms for sensor networks coordination and negotiation.
- Intelligent security proposals for distributed network sensors.
- Multi agent consensus-based systems.
- Negotiation in virtual organizations.
- Consensus-based applications for: energy, IoT, Industry 4.0, etc.
Prof. Dr. Juan Manuel Corchado
Dr. Enrique Enrique Herrera
Manuscript Submission Information
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- Machine Learning
- Artificial Intelligence