Now showing items 21-40 of 214

    • Automated Mechanism Design without Money via Machine Learning 

      Narasimhan, Harikrishna; Agarwal, Shivani Brinda; Parkes, David C. (2016)
      We use statistical machine learning to develop methods for automatically designing mechanisms in domains without money. Our goal is to find a mechanism that best approximates a given target function subject to a design ...
    • Automated Workflow Synthesis 

      Zhang, Haoqi; Horvitz, Eric; Parkes, David C. (AAAI Press, 2013)
      By coordinating efforts from humans and machines, human computation systems can solve problems that machines cannot tackle alone. A general challenge is to design efficient human computation algorithms or workflows with ...
    • Beyond Dominant Resource Fairness: Extensions, Limitations, and Indivisibilities 

      Parkes, David C.; Procaccia, Ariel; Shah, Nisarg (ACM Press, 2012)
      We study the problem of allocating multiple resources to agents with heterogeneous demands. Technological advances such as cloud computing and data centers provide a new impetus for investigating this problem under the ...
    • Bounded Rationality 

      Parkes, David C. (University of Pennsylvania, 1997)
    • Chain: A Dynamic Double Auction Framework for Matching Patient Agents 

      Bredin, Jonathan; Parkes, David C.; Duong, Quang (AI Access Foundation, 2007)
      In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by ...
    • Challenge Problem: Agent-Mediated Decentralized Information Mechanisms 

      Parkes, David C. (2002)
      Pervasive computing, driven by faster, cheaper and smaller devices, and wireless networking technology, promises to make people perpetual users of a massive and decentralized computational system. Pervasive computing blurs ...
    • Choosing Samples to Compute Heuristic-Strategy Nash Equilibrium 

      Walsh, William E.; Parkes, David C.; Das, Rajarshi (Springer, 2004)
      Auctions define games of incomplete information for which it is often too hard to compute the exact Bayesian-Nash equilibrium. Instead, the infinite strategy space is often populated with heuristic strategies, such as ...
    • Combinatorial Agency of Threshold Functions 

      Jain, Shaili; Parkes, David C. (Association for Computing Machinery, 2011)
      In this paper, we study the combinatorial agency problem introduced by Babaioff, Feldman and Nisan and resolve some open questions posed in their original paper. Our results include a characterization of the transition ...
    • A Complexity-of-Strategic-Behavior Comparison Between Schulze's Rule and Ranked Pairs 

      Parkes, David C.; Xia, Lirong (American Association for Artificial Intelligence, 2012)
      Schulze's rule and ranked pairs are two Condorcet methods that both satisfy many natural axiomatic properties. Schulze's rule is used in the elections of many organizations, including the Wikimedia Foundation, the Pirate ...
    • Computational Challenges in E-Commerce 

      Feigenbaum, Joan; Parkes, David C.; Pennock, David M. (Association for Computing Machinery, 2009)
      Economic and social sciences will drive Internet protocols and services into the future.
    • Computational Environment Design 

      Zhang, Haoqi (2012-10-26)
      The Internet has evolved into a platform on which large numbers of individuals take action and join in collaborations via crowdsourcing, social media, and electronic commerce. When designing social and economic systems on ...
    • Computational Mechanism Design 

      Parkes, David C. (Institute of Mathematical Sciences, University of Singapore, 2008)
      Computational mechanism design brings together the concern in microeconomics with decision making in the context of distributed private information and self-interest and the concern in computer science with computational ...
    • Computational-Mechanism Design: A Call to Arms 

      Dash, Rajdeep K.; Jennings, Nicholas R.; Parkes, David C. (Institute of Electrical and Electronics Engineers Computer Society, 2003)
      Game theory has developed several powerful tools for analyzing decision making in systems composed of multiple autonomous actors. Given this fact, AI practitioners would like to exploit these tools when building software ...
    • Computing cooperative solution concepts in coalitional skill games 

      Bachrach, Yoram; Parkes, David C.; Rosenschein, Jeffrey S. (Elsevier BV, 2013)
      We consider a simple model of cooperation among agents called Coalitional Skill Games (CSGs). This is a restricted form of coalitional games, where each agent has a set of skills that are required to complete various tasks. ...
    • Computing Parametric Ranking Models via Rank-Breaking 

      Soufiani, Hossein Azari; Parkes, David C.; Xia, Lirong (International Conference on Machine Learning, 2014)
      Rank breaking is a methodology introduced by Azari Soufiani et al. (2013a) for applying a Generalized Method of Moments (GMM) algorithm to the estimation of parametric ranking models. Breaking takes full rankings and breaks, ...
    • Computing Reserve Prices and Identifying the Value Distribution in Real-World Auctions with Market Dynamics 

      Walsh, William E; Parkes, David C.; Sandholm, Tuomas; Boutilier, Craig (Association for the Advancement of Artificial Intelligence, 2008)
    • Congestion Games with Distance-Based Strict Uncertainty 

      Meir, Reshef; Parkes, David C. (Association for the Advancement of Artificial Intelligence, 2015)
      We put forward a new model of congestion games where agents have uncertainty over the routes used by other agents. We take a non-probabilistic approach, assuming that each agent knows that the number of agents using an ...
    • Contrastive Learning Using Spectral Methods 

      Zou, James Yang; Hsu, Daniel; Parkes, David C.; Adams, Ryan Prescott (Neural Information Processing Systems Foundation, 2013)
      In many natural settings, the analysis goal is not to characterize a single data set in isolation, but rather to understand the difference between one set of observations and another. For example, given a background corpus ...
    • Cooperative Multiagent Search for Portfolio Selection 

      Parkes, David C.; Huberman, Bernardo A. (1998)
      We present a new multiagent model for the multiperiod portfolio selection problem. Individual agents receive a share of initial wealth, and follow an investment strategy that adjusts their portfolio as they observe movements ...
    • Correlated Voting 

      Mandal, Debmalya; Parkes, David C. (2016)
      We study the social choice problem where a group of n voters report their preferences over alternatives and a voting rule is used to select an alternative. We show that when the preferences of voters are positively correlated ...