Game Theory, Mechanism Design, Differential Privacy (and you). Aaron Roth DIMACS Workshop on Differential Privacy October 24.

Slides:



Advertisements
Similar presentations
6.896: Topics in Algorithmic Game Theory Lecture 20 Yang Cai.
Advertisements

3. Basic Topics in Game Theory. Strategic Behavior in Business and Econ Outline 3.1 What is a Game ? The elements of a Game The Rules of the.
Game Theory in Wireless and Communication Networks: Theory, Models, and Applications Lecture 6 Auction Theory Zhu Han, Dusit Niyato, Walid Saad, Tamer.
A Prior-Free Revenue Maximizing Auction for Secondary Spectrum Access Ajay Gopinathan and Zongpeng Li IEEE INFOCOM 2011, Shanghai, China.
Sep. 8, 2014 Lirong Xia Introduction to MD (mooncake design or mechanism design)
Eponine Lupo.  Questions from last time  3 player games  Games larger than 2x2—rock, paper, scissors  Review/explain Nash Equilibrium  Nash Equilibrium.
Game Theory 1. Game Theory and Mechanism Design Game theory to analyze strategic behavior: Given a strategic environment (a “game”), and an assumption.
Contracts and Mechanism Design What Contracts Accomplish Moral Hazard Adverse Selection (if time: Signaling)
1 Regret-based Incremental Partial Revelation Mechanism Design Nathanaël Hyafil, Craig Boutilier AAAI 2006 Department of Computer Science University of.
Preference Elicitation Partial-revelation VCG mechanism for Combinatorial Auctions and Eliciting Non-price Preferences in Combinatorial Auctions.
ALGORITHMIC GAME THEORY Incentive and Computation.
An Introduction to Game Theory Part I: Strategic Games
1. problem set 12 from Binmore’s Fun and Games. p.564 Ex. 41 p.565 Ex. 42.
Bundling Equilibrium in Combinatorial Auctions Written by: Presented by: Ron Holzman Rica Gonen Noa Kfir-Dahav Dov Monderer Moshe Tennenholtz.
Algorithmic Applications of Game Theory Lecture 8 1.
Algoritmi per Sistemi Distribuiti Strategici
Mechanism Design and the VCG mechanism The concept of a “mechanism”. A general (abstract) solution for welfare maximization: the VCG mechanism. –This is.
Game-Theoretic Approaches to Multi-Agent Systems Bernhard Nebel.
Lecture 1 - Introduction 1.  Introduction to Game Theory  Basic Game Theory Examples  Strategic Games  More Game Theory Examples  Equilibrium  Mixed.
Distributed Multiagent Resource Allocation In Diminishing Marginal Return Domains Yoram Bachrach(Hebew University) Jeffrey S. Rosenschein (Hebrew University)
Review: Game theory Dominant strategy Nash equilibrium
CPS Topics in Computational Economics Instructor: Vincent Conitzer Assistant Professor of Computer Science Assistant Professor of Economics
Agent Technology for e-Commerce Chapter 10: Mechanism Design Maria Fasli
An Algorithm for Automatically Designing Deterministic Mechanisms without Payments Vincent Conitzer and Tuomas Sandholm Computer Science Department Carnegie.
Computational Criticisms of the Revelation Principle Vincent Conitzer, Tuomas Sandholm AMEC V.
Workshop on Auction Theory and Practice Carnegie Mellon University 1 Strategic Information Acquisition in Auctions Kate Larson Carnegie Mellon University.
Negotiation: Markets, Rationality, and Games. Intro Once agents have discovered each other and agreed that they are interested in buying/selling, they.
Week 10 1 COS 444 Internet Auctions: Theory and Practice Spring 2008 Ken Steiglitz
Mechanism Design Traditional Algorithmic Setting Mechanism Design Setting.
On Bounded Rationality and Computational Complexity Christos Papadimitriou and Mihallis Yannakakis.
Competitive Analysis of Incentive Compatible On-Line Auctions Ron Lavi and Noam Nisan SISL/IST, Cal-Tech Hebrew University.
Yang Cai Sep 15, An overview of today’s class Myerson’s Lemma (cont’d) Application of Myerson’s Lemma Revelation Principle Intro to Revenue Maximization.
Anonymizing Web Services Through a Club Mechanism With Economic Incentives Mamata Jenamani Leszek Lilien Bharat Bhargava Department of Computer Sciences.
25 Sept 07 FF8 - Discrete Choice Data Introduction Tony O’Hagan.
Collective Revelation: A Mechanism for Self-Verified, Weighted, and Truthful Predictions Sharad Goel, Daniel M. Reeves, David M. Pennock Presented by:
Introduction to Game Theory and Strategic Interactions.
Agent-based Simulation of Financial Markets Ilker Ersoy.
A Game Theoretic Framework for Incentives in P2P Systems --- CS. Uni. California Jun Cai Advisor: Jens Graupmann.
Yang Cai Sep 8, An overview of the class Broad View: Mechanism Design and Auctions First Price Auction Second Price/Vickrey Auction Case Study:
CPS 173 Mechanism design Vincent Conitzer
6.853: Topics in Algorithmic Game Theory Fall 2011 Constantinos Daskalakis Lecture 21.
The Cost and Windfall of Manipulability Abraham Othman and Tuomas Sandholm Carnegie Mellon University Computer Science Department.
Mechanism Design CS 886 Electronic Market Design University of Waterloo.
Auction Theory תכנון מכרזים ומכירות פומביות Topic 7 – VCG mechanisms 1.
Mechanism design. Goal of mechanism design Implementing a social choice function f(u 1, …, u |A| ) using a game Center = “auctioneer” does not know the.
Regret Minimizing Equilibria of Games with Strict Type Uncertainty Stony Brook Conference on Game Theory Nathanaël Hyafil and Craig Boutilier Department.
Lecture 7 Course Summary The tools of strategy provide guiding principles that that should help determine the extent and nature of your professional interactions.
A Study of Central Auction Based Wholesale Electricity Markets S. Ceppi and N. Gatti.
Automated Mechanism Design Tuomas Sandholm Presented by Dimitri Mostinski November 17, 2004.
Price of Anarchy Georgios Piliouras. Games (i.e. Multi-Body Interactions) Interacting entities Pursuing their own goals Lack of centralized control Prediction?
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project Competitive Scheduling in Wireless Networks with Correlated Channel State Ozan.
Mechanism Design II CS 886:Electronic Market Design Sept 27, 2004.
Agent Based Models and Common Value Auctions B. Wade Brorsen.
6.853: Topics in Algorithmic Game Theory Fall 2011 Constantinos Daskalakis Lecture 22.
Designing Incentives for Boolean Games Ulle Endriss, Sarit Kraus Jerome Lang, Michael Wooldridge presented by Boris Trayvas.
Comp/Math 553: Algorithmic Game Theory Lecture 10
Game theory basics A Game describes situations of strategic interaction, where the payoff for one agent depends on its own actions as well as on the actions.
Comp/Math 553: Algorithmic Game Theory Lecture 08
CPS Mechanism design Michael Albert and Vincent Conitzer
Comp/Math 553: Algorithmic Game Theory Lecture 09
Market/Agent-Oriented Programming
Privacy as a tool for Robust Mechanism Design in Large Markets
Presented By Aaron Roth
Vincent Conitzer Mechanism design Vincent Conitzer
Vincent Conitzer CPS 173 Mechanism design Vincent Conitzer
Preference elicitation/ iterative mechanisms
Introduction to Game Theory
Information, Incentives, and Mechanism Design
Auction Theory תכנון מכרזים ומכירות פומביות
Lecture 8 Nash Equilibrium
Presentation transcript:

Game Theory, Mechanism Design, Differential Privacy (and you). Aaron Roth DIMACS Workshop on Differential Privacy October 24

Algorithms vs. Games If we control the whole system, we can just design an algorithm.

Algorithms vs. Games Otherwise, we have to design the constraints and incentives so that agents in the system work to achieve our goals.

Game Theory Model the incentives of rational, self interested agents in some fixed interaction, and predict their behavior.

Mechanism Design Model the incentives of rational, self interested agents, and design the rules of the game to shape their behavior. Can be thought of as “reverse game theory”

Relationship to Privacy “Morally” similar to private algorithm design. Mechanism DesignPrivate Algorithm Design Input data ‘belongs’ toParticipantsIndividuals Individuals experienceUtility as a function of the outcome Cost as a function of (consequences of) the outcome Must incentivize individuals to participate? YesYes?

Relationship to Privacy

Specification of a Game

0,0-1,1 1,-1 0,0-1, 1 1, -10,0

Playout of a game

Behavioral Predictions?

Dominant strategies don’t always exist… Good ol’ rock. Nuthin beats that!

Behavioral Predictions?

Behavioral Predictions Nash Equilibrium always exists (may require randomization) 33% 33% 33%

Mechanism Design

So how can privacy help?

Equivalently

Therefore

So what are the research questions?

Why are we designing mechanisms which preserve privacy Presumably because agents care about the privacy of their type. – Because it is based on medical, financial, or sensitive personal information? – Because there is some future interaction in which other players could exploit type information.

But so far this is unmodeled Could explicitly encode a cost for privacy in agent utility functions. – How should we model this? Differential privacy provides a way to quantify a worst- case upper bound on such costs But may be too strong in general. Many good ideas! [Xiao11, GR11, NOS12, CCKMV12, FL12, LR12, …] Still an open area that needs clever modeling.

How might mechanism design change? Old standards of mechanism design may no longer hold – i.e. the revelation principle: asking for your type is maximally disclosive. Example: The (usually unmodeled) first step in any data analysis task: collecting the data.

A Basic Problem

A Better Solution

A Market for Private Data Who wants $1 for their STD Status? Me! The wrong price leads to response bias

Standard Question in Game Theory What is the right price? Standard answer: Design a truthful direct revelation mechanism.

An Auction for Private Data How much for your STD Status? $1.50 $0.62 $1.25 $ Hmmmm…

Problem: Values for privacy are themselves correlated with private data! Upshot: No truthful direct revelation mechanism can guarantee non-trivial accuracy and finite payments. [GR11] There are ways around this by changing the cost model and abandoning direct revelation mechanisms [FL12,LR12]

Summary Privacy and game theory both deal with the same problem – How to compute while managing agent utilities Tools from privacy are useful in mechanism design by providing tools for managing sensitivity and noise. – We’ll see some of this in the next session. Tools from privacy may be useful for modeling privacy costs in mechanism design – We’ll see some of this in the next session – May involve rethinking major parts of mechanism design. Can ideas from game theory be used in privacy? – “Rational Privacy”?

Summary Privacy and game theory both deal with the same problem – How to compute while managing agent utilities Tools from privacy are useful in mechanism design by providing tools for managing sensitivity and noise. – We’ll see some of this in the next session. Tools from privacy may be useful for modeling privacy costs in mechanism design – We’ll see some of this in the next session – May involve rethinking major parts of mechanism design. Can ideas from game theory be used in privacy? – “Rational Privacy”?