Algorithmic Economics Papers


  • Diverse Randomized Agents Vote to Win.
    By Albert Xin Jiang, Leandro Soriano Marcolino, Ariel D. Procaccia, Tuomas Sadholm, Nisarg Shah, and Milind Tambe.
    [working paper]

  • Privacy-Preserving Coordination in Security Games.
    By Ariel D. Procaccia, Sashank J. Reddi, and Nisarg Shah.
    [working paper]

  • Electing the Most Probable Without Eliminating the Irrational: Voting Over Intransitive Domains
    By Edith Elkind, and Nisarg Shah.
    In UAI-14: Proc. 30th Conference on Uncertainty in Artificial Intelligence, pp. 182-191, 2014.
    [UAI version]

  • Modal Ranking: A Uniquely Robust Voting Rule.
    By Ioannis Caragiannis, Ariel D. Procaccia, and Nisarg Shah.
    In AAAI-14: Proc. 28th AAAI Conference on Artificial Intelligence, pp. 616-622, 2014.
    [AAAI version | Full version]

  • Betting Strategies, Market Selection, and the Wisdom of Crowds.
    By Willemien Kets, David M. Pennock, Rajiv Sethi, and Nisarg Shah.
    In AAAI-14: Proc. 28th AAAI Conference on Artificial Intelligence, pp. 735-741, 2014.
    [AAAI version]

  • On the Structure of Synergies in Cooperative Games.
    By Ariel D. Procaccia, Nisarg Shah, and Max Lee Tucker.
    In AAAI-14: Proc. 28th AAAI Conference on Artificial Intelligence, pp. 763-769, 2014.
    [AAAI version]

  • Neutrality and Geometry of Mean Voting.
    By Sébastien Lahaie, and Nisarg Shah.
    In EC-14: Proc. 15th ACM Conference on Electronic Commerce, pp. 333-350, 2014.
    [EC version | Full version]

  • Beyond Dominant Resource Fairness: Extensions, Limitations, and Indivisibilities.
    By David C. Parkes, Ariel D. Procaccia, and Nisarg Shah.
    In ACM Transactions on Economics and Computation (special issue on selected papers from EC-12, forthcoming). Supercedes the EC-12 paper below.
    [TEAC version | EC version | presentation]

  • Cooperative Max Games and Agent Failures.
    By Yoram Bachrach, Rahul Savani, and Nisarg Shah.
    In AAMAS-14: Proc. 13th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, pp. 29-36, 2014.
    [AAMAS version]

  • When Do Noisy Votes Reveal the Truth?
    By Ioannis Caragiannis, Ariel D. Procaccia, and Nisarg Shah.
    In EC-13: Proc. 14th ACM Conference on Electronic Commerce, pp. 143-160, 2013.
    [full version | EC version | presentation]

  • Defender (Mis)coordination in Security Games.
    By Albert Xin Jiang, Ariel D. Procaccia, Yundi Qian, Nisarg Shah, and Milind Tambe.
    In IJCAI-13: Proc. 23rd Intl. Joint Conference on Artificial Intelligence, pp. 220-226, 2013.
    [IJCAI version]

  • No Agent Left Behind: Dynamic Fair Division of Multiple Resources.
    By Ian Kash, Ariel D. Procaccia, and Nisarg Shah.
    In AAMAS-13: Proc. 12th Intl. Joint Conference on Autonomous Agents and Multiagent Systems, pp. 351-358, 2013.
    [full version | AAMAS version | presentation]

  • Reliability Weighted Voting Games.
    By Yoram Bachrach, and Nisarg Shah.
    In SAGT-13: Proc. 6th International Symposium on Algorithmic Game Theory, pp. 38-49, 2013.
    [full version | SAGT version]

  • Beyond Dominant Resource Fairness: Extensions, Limitations, and Indivisibilities.
    By David C. Parkes, Ariel D. Procaccia, and Nisarg Shah.
    In EC-12: Proc. 13th ACM Conference on Electronic Commerce, pp. 808-825, 2012. Superceded by the TEAC paper above.

  • Agent Failures in Totally Balanced Games and Convex Games.
    By Yoram Bachrach, Ian Kash, and Nisarg Shah.
    In WINE-12: Proc. 8th Workshop on Internet & Network Economics, pp. 15-29, 2012.
    [full version | WINE version | presentation]

  • A Maximum Likelihood Approach For Selecting Sets of Alternatives.
    By Ariel D. Procaccia, Sashank J. Reddi, and Nisarg Shah.
    In UAI-12: Proc. 28th Conference on Uncertainty in Artificial Intelligence, pp. 695-704, 2012.
    [full version | UAI version | poster]






  • Other Papers


  • Greedy Geometric Optimization Algorithms for Collection of Balls.
    By Frédéric Cazals, Tom Dreyfus, Sushant Sachdeva and Nisarg Shah.
    In Computer Graphics Forum (CGF) (forthcoming).
    [CGF version]

  • Symbolic Algorithms for Qualitative Analysis of Markov Decision Processes with Büchi Objectives.
    By Krishnendu Chatterjee, Monika Henzinger, Manas Joglekar, and Nisarg Shah.
    In Formal Methods in System Design (FMSD Journal), Volume 42, Issue 3, pp. 301-327, 2013.
    [FMSD version | CAV version | project homepage] Supercedes the CAV-11 paper below.

  • Average Case Analysis of the Classical Algorithm for Markov Decision Processes with Büchi Objectives.
    By Krishnendu Chatterjee, Manas Joglekar, and Nisarg Shah.
    In FSTTCS-12: Proc. 32nd IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science, pp. 461-473, 2012.
    [full version | FSTTCS version]

  • Balanced group-labeled graphs.
    By Manas Joglekar, Nisarg Shah and Ajit A. Diwan.
    In Discrete Mathematics, Volume 312(9), pp 1542-1549, 2012.
    [paper | presentation]

  • Symbolic Algorithms for Qualitative Analysis of Markov Decision Processes with Büchi Objectives.
    By Krishnendu Chatterjee, Monika Henzinger, Manas Joglekar, and Nisarg Shah.
    In CAV-11: Proc. 23rd International Conference on Computer Aided Verification, pp. 260-276, 2011. Superceded by the FMSD paper above.