System Model For Performing Spatial Crowdsourcing Tasks Via

System Model For Performing Spatial Crowdsourcing Tasks Via In order to test the robustness and generalization performance of each model, we generated 30 million tasks with uneven distribution spatiotemporally and whose spatial distribution varies over time, as shown in fig. 4(b). in the synthetic dataset, we also increased the proportion of multi skill tasks. We model each worker as an actor–critic agent, and generate the final task allocation scheme (i.e., optimization policy) via the game between agents (training the ma a2c am model). in addition, we design a reward function to balance the local and the global return, while obtaining a trade off between the benefit of workers and task requesters.

System Model For Performing Spatial Crowdsourcing Tasks Via 2.1 system model we consider a typical spatial crowdsourcing system. first, there is a platform receiving spatial tasks from crowdsourc ing service requesters. a spatial task is defined as follows: definition 2.1 (spatial task). a spatial task, or a task for short, is denoted by a triple s j ¼ defhl ja j;e ji, where l j is the loca tion in a. Crowdsourcing is a computing paradigm where humans are actively involved in a computing task, especially for tasks that are intrinsically easier for humans than for computers. spatial crowdsourcing is an increasing popular category of crowdsourcing in the era of mobile internet and sharing economy, where tasks are spatiotemporal and must be completed at a specific location and time. in fact. In spatial crowdsourcing system, workers are requested to physically move to particular locations to conduct the assigned tasks. multi stage tasks are composed of subtasks with dependencies, which affect task assignment efficiency and task completion rate. Guo et al. [9] review the researches of task allocation in spatial crowdsourcing and summarize a basic framework of micro task assignment, and the core strategy of the optimization model is maximizing the quality of completing tasks or minimizing the system cost while satisfying the constraints of tasks.

System Model Of Spatial Crowdsourcing Sc Download Scientific Diagram In spatial crowdsourcing system, workers are requested to physically move to particular locations to conduct the assigned tasks. multi stage tasks are composed of subtasks with dependencies, which affect task assignment efficiency and task completion rate. Guo et al. [9] review the researches of task allocation in spatial crowdsourcing and summarize a basic framework of micro task assignment, and the core strategy of the optimization model is maximizing the quality of completing tasks or minimizing the system cost while satisfying the constraints of tasks. Eward 1 (0 1).4.3 temporal weighted preference aware task assign ment (tpta) algorithmthis heuristic takes the temporal urgency of tasks into account to prioritize tasks, based on the intuition that a task which is furt. er away from its deadline is more likely to be performed in the future, and vice versa. as. A spatial task, denoted by \ (s = (s.v, s.p, s.e, s.r)\), is a task to be performed at poi s. v, published at time s. p, and will expire at s. e, with the reward of s. r. different from previous work [8], the task may appear at any point in the 2d space. in our work, a task can only be published at poi.