TY - GEN
T1 - Statistical estimation with strategic data sources in competitive settings
AU - Westenbroek, Tyler
AU - Dong, Roy
AU - Ratliff, Lillian J.
AU - Sastry, S. Shankar
N1 - Funding Information:
T. Westenbroek, R. Dong, and S. S. Sastry are with the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, 94707, USA, {westenbroekt,roydong,sastry}@eecs.berkeley.edu. L. J. Ratliff is with the Department of Electrical Engineering, University of Washington, Seattle, WA, 98195, USA, ratliffl@uw.edu. This work was supported in part by FORCES (Foundations Of Resilient CybEr-physical Systems), National Science Foundation award number CNS-1239166, NSF award number CNS 1656873, and the Republic of the Philippines Commission on Higher Education Philippine California Advanced Research Institutes (PCARI) award number IIID-2015-10.
PY - 2018/1/18
Y1 - 2018/1/18
N2 - In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.
AB - In this paper, we introduce a preliminary model for interactions in the data market. Recent research has shown ways in which a single central data aggregator can design mechanisms to ensure it receives high quality data from a collection of users, even when the sources have an aversion to producing and reporting such estimates to the aggregator. However, we have shown that these mechanisms often break down in more realistic models, where multiple data aggregators are in competition for the users' data. We formulate the competition that arises between the aggregators as a game, and show this game admits either no Nash equilibria, or a continuum of Nash Equilibria. In the latter case, there is a fundamental ambiguity in who bears the burden of incentivizing different data sources. We are also able to calculate the price of anarchy, which measures how much social welfare is lost between the Nash equilibrium and the social optimum, i.e. between non-cooperative strategic play and cooperation.
UR - http://www.scopus.com/inward/record.url?scp=85046120863&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046120863&partnerID=8YFLogxK
U2 - 10.1109/CDC.2017.8264398
DO - 10.1109/CDC.2017.8264398
M3 - Conference contribution
AN - SCOPUS:85046120863
T3 - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
SP - 4994
EP - 4999
BT - 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 56th IEEE Annual Conference on Decision and Control, CDC 2017
Y2 - 12 December 2017 through 15 December 2017
ER -