FDRL-PPO is a federated PPO-based RL method enabling mobile units to learn efficient task participation strategies in dynamic crowdsensing without complete system information or raw data sharing.
Delay- and incentive- aware crowdsensing: A stable matching approach for coverage maxi- mization,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Federated Reinforcement Learning for Efficient Mobile Crowdsensing under Incomplete Information
FDRL-PPO is a federated PPO-based RL method enabling mobile units to learn efficient task participation strategies in dynamic crowdsensing without complete system information or raw data sharing.