GLOBECOM 2022 - 2022 IEEE Global Communications Conference 2022
DOI: 10.1109/globecom48099.2022.10000860
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Environment-Driven Task Allocation in Heterogeneous Spatial Crowdsourcing

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Cited by 2 publications
(1 citation statement)
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“…Sun et al [13] introduced the EDPG-Assignment framework, amalgamating action embedding and neighborhood deep deterministic policy gradient to intelligently assign tasks for interactive spatial crowdsourcing applications. To address the disregarded heterogeneity of spatial crowdsourcing tasks, [20] proposed the TA-DSAC algorithm solution, training agents within spatio-temporal constraints. Ho et al [21] framed the interruption issue in microtask competition in crowdsourcing as a Markov decision process.…”
Section: Related Workmentioning
confidence: 99%
“…Sun et al [13] introduced the EDPG-Assignment framework, amalgamating action embedding and neighborhood deep deterministic policy gradient to intelligently assign tasks for interactive spatial crowdsourcing applications. To address the disregarded heterogeneity of spatial crowdsourcing tasks, [20] proposed the TA-DSAC algorithm solution, training agents within spatio-temporal constraints. Ho et al [21] framed the interruption issue in microtask competition in crowdsourcing as a Markov decision process.…”
Section: Related Workmentioning
confidence: 99%