Intervention with Private Information, Imperfect Monitoring and Costly Communication

被引:12
作者
Canzian, Luca [1 ]
Xiao, Yuanzhang [1 ]
Zame, William [2 ]
Zorzi, Michele [3 ]
van der Schaar, Mihaela [1 ]
机构
[1] Univ Calif Los Angeles, Dept Elect Engn, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Dept Econ, Los Angeles, CA 90095 USA
[3] Univ Padua, Dept Informat Engn, I-35131 Padua, Italy
基金
美国国家科学基金会;
关键词
Game theory; incomplete information; mechanism design; intervention; resource allocation; COOPERATION; NETWORKS;
D O I
10.1109/TCOMM.2013.061013.120558
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper studies the interaction between a designer and a group of strategic and self-interested users who possess information the designer does not have. Because the users are strategic and self-interested, they will act to their own advantage, which will often be different from the interest of the designer, even if the latter is benevolent and seeks to maximize (some measure of) social welfare. In the settings we consider, the designer and the users can communicate (perhaps with noise), the designer can observe the actions of the users (perhaps with error) and the designer can commit to (plans of) actions - interventions - of its own. The designer's problem is to construct and implement a mechanism that provides incentives for the users to communicate and act in such a way as to further the interest of the designer - despite the fact that they are strategic and self-interested and possess private information. To address the designer's problem we propose a general and flexible framework that applies to many scenarios. To illustrate the usefulness of this framework, we discuss some simple examples, leaving further applications to other papers. In an important class of environments, we find conditions under which the designer can obtain its benchmark optimum - the utility that could be obtained if it had all information and could command the actions of the users - and conditions under which it cannot. More broadly we are able to characterize the solution to the designer's problem, even when it does not yield the benchmark optimum. Because the optimal mechanism may be difficult to construct and implement, we also propose a simpler and more readily implemented mechanism that, while falling short of the optimum, still yields the designer a "good" result.
引用
收藏
页码:3192 / 3205
页数:14
相关论文
共 50 条
  • [31] Optimal voting schemes with costly information acquisition
    Gershkov, Alex
    Szentes, Balazs
    JOURNAL OF ECONOMIC THEORY, 2009, 144 (01) : 36 - 68
  • [32] Information elicitation for aggregate demand prediction with costly forecasting
    Egri, Peter
    AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS, 2016, 30 (04) : 681 - 696
  • [33] Second and third party punishment under costly monitoring
    Goeschl, Timo
    Jarke, Johannes
    JOURNAL OF ECONOMIC PSYCHOLOGY, 2016, 54 : 124 - 133
  • [34] Lossless abstraction of imperfect information games
    Gilpin, Andrew
    Sandholm, Tuomas
    JOURNAL OF THE ACM, 2007, 54 (05)
  • [35] Pushdown module checking with imperfect information
    Aminof, Benjamin
    Legay, Axel
    Murano, Aniello
    Serre, Olivier
    Vardi, Moshe Y.
    INFORMATION AND COMPUTATION, 2013, 223 : 1 - 17
  • [36] Information elicitation for aggregate demand prediction with costly forecasting
    Péter Egri
    Autonomous Agents and Multi-Agent Systems, 2016, 30 : 681 - 696
  • [37] Misconduct and Reputation under Imperfect Information
    Annan, Francis
    JOURNAL OF POLITICAL ECONOMY, 2025, 133 (05) : 1460 - 1496
  • [38] Imperfect information facilitates the evolution of reciprocity
    Kurokawa, Shun
    MATHEMATICAL BIOSCIENCES, 2016, 276 : 114 - 120
  • [39] THE FOLK THEOREM WITH IMPERFECT PUBLIC INFORMATION
    FUDENBERG, D
    LEVINE, D
    MASKIN, E
    ECONOMETRICA, 1994, 62 (05) : 997 - 1039
  • [40] On Demand Response Management Performance Optimization for Microgrids Under Imperfect Communication Constraints
    Yang, Chao
    Yao, Junmei
    Lou, Wei
    Xie, Shengli
    IEEE INTERNET OF THINGS JOURNAL, 2017, 4 (04): : 881 - 893