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Decentralized Online Learning in Task Assignment Games for Mobile Crowdsensing
The task assignment problem is modeled as a matching game considering the MCSP's and MUs' individual goals while the MUs learn their efforts online.
Context-Aware Hierarchical Online Learning for Performance Maximization in Mobile Crowdsourcing
In our algorithm, a local controller (LC) in the mobile device of a worker regularly observes the worker's context, her/his decisions to accept or decline tasks and the quality in completing tasks.
Context-Aware Proactive Content Caching with Service Differentiation in Wireless Networks
We derive a sublinear regret bound, which characterizes the learning speed and proves that our algorithm converges to the optimal cache content placement strategy in terms of maximizing the number of cache hits.
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