Titlebook: Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collectio; 17th International C Yves Demazeau,Er

Irremediable

https://doi.org/10.1007/b138337ne learning techniques have been widely used in this area. Since smartphones and their applications are the parts of daily life, they can be very helpful in data gathering and online learning in HAR problems. In this paper, a new hierarchical neural network structure with the hierarchical learning m

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抱怨

https://doi.org/10.1007/b138337ver autonomous agents (e.g., sheep, cattle) for containment or transportation. Accordingly, plenty of research has focused on designing algorithms for robotic agents to solve such tasks. Almost no research, however, has utilized this task to investigate human-human or human-machine interactions, eve

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https://doi.org/10.1007/b138337sonal data always bring privacy and security issues. This work wants to promote a balanced solution between the need of personal information and the user’s privacy expectations. We propose a solution to overcome these issues, and don’t compromise the balance between security and personal comfort bas

去掉

https://doi.org/10.1007/b138337onsidering citizens, individual multi-modal mobility, and heterogeneous traffic groups. They have different interests, goals and regulation, so new multi-objective cost functions and control systems are required. . is structured around a novel control paradigm, based on the generation and distributi

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