Hassan, Umair Ul and Curry, Edward
(2014)
A Multi-armed Bandit Approach to Online Spatial Task Assignment.
In: 14 IEEE International Conference on Ubiquitous Intelligence and Computing, 9-12 Dec. 2014, Bali, Indonesia.
Abstract
Spatial crowdsourcing uses workers for performing
tasks that require travel to different locations in the physical
world. This paper considers the online spatial task assignment
problem. In this problem, spatial tasks arrive in an online
manner and an appropriate worker must be assigned to each
task. However, outcome of an assignment is stochastic since the
worker can choose to accept or reject the task. Primary goal of the
assignment algorithm is to maximize the number of successful assignments over all tasks. This presents an exploration-exploitation
challenge; the algorithm must learn the task acceptance behavior
of workers while selecting the best worker based on the previous
learning. We address this challenge by defining a framework for
online spatial task assignment based on the multi-armed bandit
formalization of the problem. Furthermore, we adapt a contextual
bandit algorithm to assign a worker based on the spatial features
of tasks and workers. The algorithm simultaneously adapts
the worker assignment strategy based on the observed task
acceptance behavior of workers. Finally, we present an evaluation
methodology based on a real world dataset, and evaluate the
performance of the proposed algorithm against the baseline
algorithms. The results demonstrate that the proposed algorithm
performs better in terms of the number of successful assignments.
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Keywords: |
spatial crowdsourcing; task assignment; multi-armed bandit; |
| Academic Unit: |
Faculty of Social Sciences > School of Business |
| Item ID: |
16012 |
| Identification Number: |
https://doi.org/10.1109/UIC-ATC-ScalCom.2014.68 |
| Depositing User: |
Souleiman Hasan
|
| Date Deposited: |
30 May 2022 12:00 |
| Refereed: |
Yes |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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