{"type":"ScholarlyArticle","title":"Adversarial Task Assignment","authors":[{"name":"Chen Hajaj","slug":"chen-hajaj","given":"Chen","family":"Hajaj","affiliation":"Electrical Engineering and Computer Science Vanderbilt University , Nashville , Tennses"},{"name":"Yevgeniy Vorobeychik","slug":"yevgeniy-vorobeychik","given":"Yevgeniy","family":"Vorobeychik","affiliation":"Electrical Engineering and Computer Science Vanderbilt University , Nashville , Tennses"}],"abstract":"The problem of task assignment to workers is of\r\nlong-standing fundamental importance. Examples of this include the classical\r\nproblem of assigning computing tasks to nodes in a distributed computing\r\nenvironment, assigning jobs to robots, and crowdsourcing. Extensive research\r\ninto this problem generally addresses important issues such as uncertainty and\r\nincentives. However, the problem of adversarial tampering with the task\r\nassignment process has not received as much attention.  We are concerned with a particular adversarial setting in\r\ntask assignment where an attacker may target a set of workers in order to\r\nprevent the tasks assigned to these workers from being completed. For the case when all tasks are homogeneous, we provide an\r\nefficient algorithm for computing the optimal assignment. When tasks are\r\nheterogeneous, we show that the adversarial assignment problem is NP-Hard, and present an\r\nalgorithm for solving it approximately. Our theoretical results are accompanied\r\nby extensive simulation results showing the effectiveness of our algorithms.","doi":"10.24963/ijcai.2018/526","url":"https://ijcai.org/proceedings/2018/526","pdf":"https://ijcai.org/proceedings/2018/0526.pdf","markdown":"https://ijcai.org/proceedings/2018/526.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/526","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Multidisciplinary Topics and Applications","track":"Main track","number":526,"pages":{"first":3783,"last":3789},"keywords":["Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems","Agent-based and Multi-agent Systems: Resource Allocation","Multidisciplinary Topics and Applications: Security and Privacy"],"videos":[],"references":[{"position":1,"raw":"[Alighanbari and How, 2005] Mehdi Alighanbari and Jonathan P How. Cooperative task assignment of un- manned aerial vehicles in adversarial environments. In American Control Conference, 2005., pages 4661-4666. IEEE, 2005.","title":"Cooperative task assignment of unmanned aerial vehicles in adversarial environments","authors":"Mehdi Alighanbari, Jonathan P How","year":"2005","venue":"American Control Conference","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Alistarh et al., 2012] Dan Alistarh, Michael A Bender, Seth Gilbert, and Rachid Guerraoui. How to allocate tasks asyn- chronously. In IEEE Annual Symposium on Foundations of Computer Science (FOCS), pages 331-340. IEEE, 2012.","title":"How to allocate tasks asynchronously","authors":"Dan Alistarh, Michael A Bender, Seth Gilbert, Rachid Guerraoui","year":"2012","venue":"IEEE Annual Symposium on Foundations of Computer Science (FOCS)","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Alon et al., 2015] Noga Alon, Michal Feldman, Omer Lev, and Moshe Tennenholtz. How robust is the wisdom of the crowds? In Proceedings of the International Joint Confer- ences on Artificial Intelligence, pages 2055-2061, 2015.","title":"How robust is the wisdom of the crowds?","authors":"Noga Alon, Michal Feldman, Omer Lev, Moshe Tennenholtz","year":"2015","venue":"Proceedings of the International Joint Conferences on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2015/291"},{"position":4,"raw":"[Carvalho et al., 2016] Arthur Carvalho, Stanko Dimitrov, and Kate Larson. How many crowdsourced workers should a requester hire? Annals of Mathematics and Arti- ficial Intelligence, 78(1):45-72, 2016.","title":"How many crowdsourced workers should a requester hire?","authors":"Arthur Carvalho, Stanko Dimitrov, Kate Larson","year":"2016","venue":"Annals of Mathematics and Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Chen et al., 2011] Yudong Chen, Huan Xu, Constantine Caramanis, and Sujay Sanghavi. Robust matrix comple- tion and corrupted columns. In International Conference on Machine Learning (ICML), pages 873-880, 2011.","title":"Robust matrix completion and corrupted columns","authors":"Yudong Chen, Huan Xu, Constantine Caramanis, Sujay Sanghavi","year":"2011","venue":"International Conference on Machine Learning (ICML)","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Chen et al., 2013] Yudong Chen, Constantine Caramanis, and Shie Mannor. Robust sparse regression under adver- sarial corruption. In International Conference on Machine Learning (ICML), pages 774-782, 2013.","title":"Robust sparse regression under adversarial corruption","authors":"Yudong Chen, Constantine Caramanis, Shie Mannor","year":"2013","venue":"International Conference on Machine Learning (ICML)","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Chen et al., 2014] Richard Li-Yang Chen, Amy Cohn, Neng Fan, and Ali Pinar. Contingency-risk informed power system design. IEEE Transactions on Power Sys- tems, 29(5):2087 -2096, 2014.","title":"Contingency-risk informed power system design","authors":"Richard Li-Yang Chen, Amy Cohn, Neng Fan, Ali Pinar","year":"2014","venue":"IEEE Transactions on Power Systems","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Conitzer and Sandholm, 2006] Vincent Conitzer and Tuo- mas Sandholm. Computing the optimal strategy to commit to. In Proceedings of the ACM Conference on Electronic Commerce (EC), pages 82-90, 2006.","title":"Computing the optimal strategy to commit to","authors":"Sandholm Conitzer, Vincent Conitzer, Tuomas Sandholm","year":"2006","venue":"Proceedings of the ACM Conference on Electronic Commerce (EC)","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Dai et al., 2011] Peng Dai, Daniel Sabby Weld, et al. Ar- tificial intelligence for artificial artificial intelligence. In Proceedings of AAAI, pages 1153-1159, 2011.","title":"Artificial intelligence for artificial artificial intelligence","authors":"Peng Dai, Daniel Sabby Weld","year":"2011","venue":"Proceedings of AAAI","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Elmalech et al., 2016] Avshalom Elmalech, David Sarne, Esther David, and Chen Hajaj. Extending workers' at- tention span through dummy events. In Proceedings of HCOMP, 2016.","title":"Extending workers' attention span through dummy events","authors":"Avshalom Elmalech, David Sarne, Esther David, Chen Hajaj","year":"2016","venue":"Proceedings of HCOMP","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Feng et al., 2014] Jiashi Feng, Huan Xu, Shie Mannor, and Shuicheng Yan. Robust logistic regression and classifica- tion. In NIPS, pages 253-261, 2014.","title":"Robust logistic regression and classification","authors":"Feng","year":"2014","venue":"NIPS","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Ghosh et al., 2011] Arpita Ghosh, Satyen Kale, and Preston McAfee. Who moderates the moderators? crowdsourcing abuse detection in user-generated content. In Proceedings of the ACM Conference on Electronic Commerce (EC), pages 167-176, 2011.","title":"Who moderates the moderators? crowdsourcing abuse detection in user-generated content","authors":"Arpita Ghosh, Satyen Kale, Preston Mcafee","year":"2011","venue":"Proceedings of the ACM Conference on Electronic Commerce (EC)","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Gu et al., 2005] Dazhang Gu, Frank Drews, and Lonnie Welch. Robust task allocation for dynamic distributed real- time systems subject to multiple environmental parame- ters. In Distributed Computing Systems, 2005. ICDCS 2005. Proceedings. 25th IEEE International Conference on, pages 675-684. IEEE, 2005.","title":"Robust task allocation for dynamic distributed realtime systems subject to multiple environmental parameters","authors":"Gu","year":"2005","venue":"ICDCS 2005. Proceedings. 25th IEEE International Conference on","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Jones et al., 2006] Edward Gil Jones, Brett Browning, M Bernardine Dias, Brenna Argall, Manuela Veloso, and Anthony Stentz. Dynamically formed heterogeneous robot teams performing tightly-coordinated tasks. In Proceed- ings of the IEEE International Conference on Robotics and Automation (ICRA), pages 570-575. IEEE, 2006.","title":"Dynamically formed heterogeneous robot teams performing tightly-coordinated tasks","authors":"Edward Gil, Jones, Brett Browning, Bernardine Dias, Brenna Argall, Manuela Veloso, Anthony Stentz","year":"2006","venue":"Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Kleywegt et al., 2002] Anton J Kleywegt, Alexander Shapiro, and Tito Homem-de Mello. The sample average approximation method for stochastic discrete optimiza- tion. SIAM Journal on Optimization, 12(2):479-502, 2002.","title":"The sample average approximation method for stochastic discrete optimization","authors":"Kleywegt","year":"2002","venue":"SIAM Journal on Optimization","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Korzhyk et al., 2010] Dmytro Korzhyk, Vincent Conitzer, and Ronald Parr. Complexity of computing optimal stack- elberg strategies in security resource allocation games. In Proceedings of AAAI, pages 805-810, 2010.","title":"Complexity of computing optimal stackelberg strategies in security resource allocation games","authors":"Dmytro Korzhyk, Vincent Conitzer, Ronald Parr","year":"2010","venue":"Proceedings of AAAI","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Liu and Chen, 2017] Yang Liu and Yiling Chen. Sequen- tial peer prediction: Learning to elicit effort using posted prices. In Proceedings of AAAI, pages 607-613, 2017.","title":"Sequential peer prediction: Learning to elicit effort using posted prices","authors":"Chen ; Liu, Yang Liu, Yiling Chen","year":"2017","venue":"Proceedings of AAAI","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Liu et al., 2017] Chang Liu, Bo Li, Yevgeniy Vorobeychik, and Alina Oprea. Robust linear regression against training data poisoning. In ACM Workshop on Artificial Intelli- gence and Security, 2017.","title":"Robust linear regression against training data poisoning","authors":"Chang Liu, Bo Li, Yevgeniy Vorobeychik, Alina Oprea","year":"2017","venue":"ACM Workshop on Artificial Intelligence and Security","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Manino et al., 2016] Edoardo Manino, Long Tran-Thanh, and Nicholas R Jennings. Efficiency of active learning for the allocation of workers on crowdsourced classification tasks. arXiv preprint arXiv:1610.06106, 2016.","title":"Efficiency of active learning for the allocation of workers on crowdsourced classification tasks","authors":"Edoardo Manino, Long Tran-Thanh, Nicholas R Jennings","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Mason and Suri, 2012] Winter Mason and Siddharth Suri. Conducting behavioral research on amazon's mechanical turk. Behavior research methods, 44(1):1-23, 2012.","title":"Winter Mason and Siddharth Suri. Conducting behavioral research on amazon's mechanical turk","authors":"Suri Mason","year":"2012","venue":"Behavior research methods","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Sheng et al., 2008] Victor S Sheng, Foster Provost, and Panagiotis G Ipeirotis. Get another label? improving data quality and data mining using multiple, noisy labelers. In Proceedings of ACM SIGKDD, pages 614-622, 2008.","title":"Get another label? improving data quality and data mining using multiple, noisy labelers","authors":"Foster Victor S Sheng, Panagiotis G Provost, Ipeirotis","year":"2008","venue":"Proceedings of ACM SIGKDD","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Singla and Krause, 2013] Adish Singla and Andreas Krause. Truthful incentives in crowdsourcing tasks using regret minimization mechanisms. In Proceedings of the international conference on World Wide Web, pages 1167-1178. ACM, 2013.","title":"Truthful incentives in crowdsourcing tasks using regret minimization mechanisms","authors":"Krause Singla, Adish Singla, Andreas Krause","year":"2013","venue":"Proceedings of the international conference on World Wide Web","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Stackelberg, 1952] Heinrich von Stackelberg. Theory of the market economy. 1952.","title":"Theory of the market economy","authors":"Stackelberg","year":"1952","venue":null,"doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Steinhardt et al., 2016] Jacob Steinhardt, Gregory Valiant, and Moses Charikar. Avoiding imposters and delinquents: Adversarial crowdsourcing and peer prediction. In NIPS, pages 4439-4447, 2016.","title":"Avoiding imposters and delinquents: Adversarial crowdsourcing and peer prediction","authors":"Jacob Steinhardt, Gregory Valiant, Moses Charikar","year":"2016","venue":"NIPS","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Stone and Veloso, 1999] Peter Stone and Manuela Veloso. Task decomposition, dynamic role assignment, and low- bandwidth communication for real-time strategic team- work. Artificial Intelligence, 110(2):241-273, 1999.","title":"Peter Stone and Manuela Veloso. Task decomposition, dynamic role assignment, and lowbandwidth communication for real-time strategic teamwork","authors":"Veloso Stone","year":"1999","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Tambe, 2011] Milind Tambe. Security and game theory: al- gorithms, deployed systems, lessons learned. Cambridge University Press, 2011.","title":"Security and game theory: algorithms, deployed systems, lessons learned","authors":"Milind Tambe","year":"2011","venue":null,"doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Tran-Thanh et al., 2014] Long Tran-Thanh, Trung Dong Huynh, Avi Rosenfeld, Sarvapali D Ramchurn, and Nicholas R Jennings. Budgetfix: budget limited crowd- sourcing for interdependent task allocation with quality guarantees. In Proceedings of AAMAS, pages 477-484, 2014.","title":"Budgetfix: budget limited crowdsourcing for interdependent task allocation with quality guarantees","authors":"Tran-Thanh","year":"2014","venue":"Proceedings of AAMAS","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Xu et al., 2010] Huan Xu, Constantine Caramanis, and Su- jay Sanghavi. Robust PCA via outlier pursuit. In NIPS, pages 2496-2504, 2010.","title":"Robust PCA via outlier pursuit","authors":"Huan Xu, Constantine Caramanis, Sujay Sanghavi","year":"2010","venue":"NIPS","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}