Research Article
Dynamic Task Assignment Framework for Mobile Crowdsensing with Deep Reinforcement Learning
Table 1
Experiment definition parameters.
| Parameters | Settings |
| RM (capacity of the replay memory) | 50000 | (probability of random selection) | 0.2-0.1 | (steps to update the target network) | 300 | (discount factor) | 0.95 | (learning rate) | 0.001 | Minibatch size | 64 | Sliding window | 50 | (maximum training episodes in Algorithm 1) | 50000 | (the maximum number of a task completed) | 1-3 | Periods in Gowalla | 24 | Periods in Foursquare | 40 | Number of workers in Gowalla | [60,70,80,90,100] | Number of workers in Foursquare | [30,40,50,60,70] | Task test sets days in Gowalla | [7,9,10,12] | Task test sets days in Foursquare | [10,12,15,20] | (perception radius) | [1 km, 2 km, 3 km] |
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