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Crowdsourcing has emerged as a paradigm for leveraging human intelligence and activity to solve a wide range of tasks. However, strategic workers will find enticement in their self-interest to free-ride and attack in a crowdsourcing contest…

Computer Science and Game Theory · Computer Science 2018-01-01 Jianfeng Lu , Yun Xin , Zhao Zhang , Shaojie Tang , Songyuan Yan , Changbing Tang

Many distributed systems are subject to the Sybil attack, where an adversary subverts system operation by emulating behavior of multiple distinct nodes. Most recent work to address this problem leverages social networks to establish trust…

Networking and Internet Architecture · Computer Science 2012-01-16 Frank Li , Prateek Mittal , Matthew Caesar , Nikita Borisov

Airdrops issued by platforms are to distribute tokens, drive user adoption, and promote decentralized services. The distributions attract airdrop hunters (attackers), who exploit the system by employing Sybil attacks, i.e., using multiple…

Computer Science and Game Theory · Computer Science 2025-03-19 Junliang Luo , Hong Kang , Shuhao Zheng , Xue Liu

Designing auctions to incentivize buyers to invite new buyers via their social connections is a new trend in mechanism design. The challenge is that buyers are competitors and we need to design proper incentives for them to invite each…

Computer Science and Game Theory · Computer Science 2023-03-07 Haoxin Liu , Yao Zhang , Dengji Zhao

As the driving force of crowdsourcing is the interaction among participants, various incentive mechanisms have been proposed to attract sufficient participants. However, the existing works assume that all the providers always meet the…

Human-Computer Interaction · Computer Science 2017-07-04 Duin Back , Bong Jun Choi , Jing Chen

Traditionally, peer-to-peer systems have relied on altruism and reciprocity. Although incentive-based models have gained prominence in new-generation peer-to-peer systems, it is essential to recognize the continued importance of cooperative…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-15 Bulat Nasrulin , Rowdy Chotkan , Johan Pouwelse

Exploration efficiency is a challenging problem in multi-agent reinforcement learning (MARL), as the policy learned by confederate MARL depends on the collaborative approach among multiple agents. Another important problem is the less…

Machine Learning · Computer Science 2019-12-30 Qisheng Wang , Qichao Wang

Crowdsourcing has gained immense popularity in machine learning applications for obtaining large amounts of labeled data. Crowdsourcing is cheap and fast, but suffers from the problem of low-quality data. To address this fundamental…

Computer Science and Game Theory · Computer Science 2015-12-17 Nihar B. Shah , Dengyong Zhou

To ensure that social networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly…

Computer Science and Game Theory · Computer Science 2015-06-17 Jie Xu , Yangbo Song , Mihaela van der Schaar

The problem of Profit Maximization asks to choose a limited number of influential users from a given social network such that the initial activation of these users maximizes the profit earned at the end of the diffusion process. This…

Social and Information Networks · Computer Science 2026-02-03 Poonam Sharma , Suman Banerjee

Incentives are key to the success of crowdsourcing which heavily depends on the level of user participation. This paper designs an incentive mechanism to motivate a heterogeneous crowd of users to actively participate in crowdsourcing…

Multiagent Systems · Computer Science 2018-12-13 Tie Luo , Salil S. Kanhere , Sajal K. Das , Hwee-Pink Tan

Campaigners are increasingly using online social networking platforms for promoting products, ideas and information. A popular method of promoting a product or even an idea is incentivizing individuals to evangelize the idea vigorously by…

Social and Information Networks · Computer Science 2016-06-17 Bhushan Kotnis , Joy Kuri

Recent research has demonstrated the potential of reinforcement learning (RL) in enabling effective multi-robot collaboration, particularly in social dilemmas where robots face a trade-off between self-interests and collective benefits.…

Robotics · Computer Science 2023-08-01 Shahab Nikkhoo , Zexin Li , Aritra Samanta , Yufei Li , Cong Liu

Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and etc.) emerged in recent years that allow requesters from all around the world to post tasks and seek help from an equally global pool of workers. However, intrinsic…

Artificial Intelligence · Computer Science 2011-08-11 Yu Zhang , Mihaela van der Schaar

Decentralized reputation systems are emerging as promising mechanisms to enhance the effectiveness of token-based economies. Unlike traditional monetary incentives, these systems reward participants based on the actual value of their…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-22 Bulat Nasrulin , Georgy Ishmaev , Johan Pouwelse

Preference-based Reinforcement Learning (PbRL) provides a way to learn high-performance policies in environments where the reward signal is hard to specify, avoiding heuristic and time-consuming reward design. However, PbRL can suffer from…

Machine Learning · Computer Science 2025-07-02 Chenyang Cao , Miguel Rogel-García , Mohamed Nabail , Xueqian Wang , Nicholas Rhinehart

The reward signal plays a central role in defining the desired behaviors of agents in reinforcement learning (RL). Rewards collected from realistic environments could be perturbed, corrupted, or noisy due to an adversary, sensor error, or…

Machine Learning · Computer Science 2025-03-12 Xi Chen , Zhihui Zhu , Andrew Perrault

Social networks have increasingly become important and popular in modern times. Moreover, the influence of social networks plays a vital role in various organizations including government organizations, academic research or corporate…

Social and Information Networks · Computer Science 2022-03-01 WC Yeh , CL Huang , TY Hsu , Z Liu , SY Tan

This paper provides a novel solution to a task allocation problem, by which a group of agents decides on the assignment of a discrete set of tasks in a distributed manner. In this setting, heterogeneous agents have individual preferences…

Optimization and Control · Mathematics 2023-11-02 Nirabhra Mandal , Mohammad Khajenejad , Sonia Martínez

We study a cost sharing problem derived from bug bounty programs, where agents gain utility by the amount of time they get to enjoy the cost shared information. Once the information is provided to an agent, it cannot be retracted. The goal,…

Computer Science and Game Theory · Computer Science 2020-06-26 Mingyu Guo , Yong Yang , Muhammad Ali Babar