Swarm intelligence research: From bio-inspired single-population swarm intelligence to human-machine hybrid swarm intelligence
GY Wang, DD Cheng, DY **a, HH Jiang - Machine Intelligence Research, 2023 - Springer
Swarm intelligence has become a hot research field of artificial intelligence. Considering the
importance of swarm intelligence for the future development of artificial intelligence, we …
importance of swarm intelligence for the future development of artificial intelligence, we …
Cooperative task assignment in spatial crowdsourcing via multi-agent deep reinforcement learning
P Zhao, X Li, S Gao, X Wei - Journal of Systems Architecture, 2022 - Elsevier
With the rapid development of mobile Internet, spatial crowdsourcing (SC) has become an
emerging paradigm with many applications. As a key challenge in SC, the problem of task …
emerging paradigm with many applications. As a key challenge in SC, the problem of task …
Context-and fairness-aware in-process crowdworker recommendation
Identifying and optimizing open participation is essential to the success of open software
development. Existing studies highlighted the importance of worker recommendation for …
development. Existing studies highlighted the importance of worker recommendation for …
群智协同任务分配研究综述.
陈宝童， 王丽清， 蒋晓敏… - Journal of Computer …, 2021 - search.ebscohost.com
任务分配是群智协同计算和众包中的核心问题之一, 即通过设计合理的任务分配策略,
在满足任务约束条件下, 将群智任务分配给合适的工作者, 以提高群智任务的完成效率和结果 …
在满足任务约束条件下, 将群智任务分配给合适的工作者, 以提高群智任务的完成效率和结果 …
Context-aware in-process crowdworker recommendation
Identifying and optimizing open participation is essential to the success of open software
development. Existing studies highlighted the importance of worker recommendation for …
development. Existing studies highlighted the importance of worker recommendation for …
An end-to-end deep RL framework for task arrangement in crowdsourcing platforms
In this paper, we propose a Deep Reinforcement Learning (RL) framework for task
arrangement, which is a critical problem for the success of crowdsourcing platforms …
arrangement, which is a critical problem for the success of crowdsourcing platforms …
Learning to recommend items to wikidata editors
Wikidata is an open knowledge graph built by a global community of volunteers. As it
advances in scale, it faces substantial challenges around editor engagement. These …
advances in scale, it faces substantial challenges around editor engagement. These …
A task recommendation scheme for crowdsourcing based on expertise estimation
In crowdsourcing systems, tasks are accomplished by a crowd of workers in a competitive
mode. Since tasks are diverse in nature, workers face difficulties in selecting a task. This …
mode. Since tasks are diverse in nature, workers face difficulties in selecting a task. This …
Deep learning-based recommendation method for top-K tasks in software crowdsourcing systems.
Z Peng, D Wan, A Wang, X Lu… - Journal of Industrial & …, 2023 - search.ebscohost.com
The task personalized recommendation problems in software crowdsourcing systems have
unique characteristics, ie, large task flow, high task complexity, long development cycle …
unique characteristics, ie, large task flow, high task complexity, long development cycle …
Crowd-enabled multiple Pareto-optimal queries for multi-criteria decision-making services
B Yin, P Zhang, B Xu, H Chen, Y Ji - Future Generation Computer Systems, 2023 - Elsevier
The widespread usage of crowdsourcing systems, which leverage human intelligence to do
computer-hard tasks, has created an urgent need to combine crowdsourcing with automated …
computer-hard tasks, has created an urgent need to combine crowdsourcing with automated …