Game Theory: Spring 2017

Similar documents
Multiagent Systems: Spring 2006

COMP/MATH 553 Algorithmic Game Theory Lecture 8: Combinatorial Auctions & Spectrum Auctions. Sep 29, Yang Cai

Lecture 7 - Auctions and Mechanism Design

Multiagent Systems: Rational Decision Making and Negotiation

Recap Beyond IPV Multiunit auctions Combinatorial Auctions Bidding Languages. Multi-Good Auctions. CPSC 532A Lecture 23.

Introduction to Auctions

1 Mechanism Design (incentive-aware algorithms, inverse game theory)

An Introduction to Iterative Combinatorial Auctions

Software Frameworks for Advanced Procurement Auction Markets

1 Mechanism Design (incentive-aware algorithms, inverse game theory)

Verifying Dominant Strategy Equilibria in Auctions

Traditional auctions such as the English SOFTWARE FRAMEWORKS FOR ADVANCED PROCUREMENT

Searching for the Possibility Impossibility Border of Truthful Mechanism Design

Diffusion Mechanism Design

Silvia Rossi. Auctions. Lezione n. Corso di Laurea: Informatica. Insegnamento: Sistemi multi-agente. A.A.

Three New Connections Between Complexity Theory and Algorithmic Game Theory. Tim Roughgarden (Stanford)

Activity Rules and Equilibria in the Combinatorial Clock Auction

Sponsored Search Markets

1 Mechanism Design (incentive-aware algorithms, inverse game theory)

Intro to Algorithmic Economics, Fall 2013 Lecture 1

Note on webpage about sequential ascending auctions

CS364B: Frontiers in Mechanism Design Lecture #1: Ascending and Ex Post Incentive Compatible Mechanisms

Mechanism Design in Social Networks

Bidding Clubs in First-Price Auctions Extended Abstract

Methods for boosting revenue in combinatorial auctions

Online Combinatorial Auctions

Competitive Markets. Jeffrey Ely. January 13, This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License.

A Cooperative Approach to Collusion in Auctions

Introduction to Multi-Agent Programming

Competitive Analysis of Incentive Compatible On-line Auctions

Price of anarchy in auctions & the smoothness framework. Faidra Monachou Algorithmic Game Theory 2016 CoReLab, NTUA

Auction Theory: an Introduction

Combinatorial Auctions

Multiagent Resource Allocation 1

CS269I: Incentives in Computer Science Lecture #16: Revenue-Maximizing Auctions

Non-decreasing Payment Rules in Combinatorial Auctions

Optimal Shill Bidding in the VCG Mechanism

Characterization of Strategy/False-name Proof Combinatorial Auction Protocols: Price-oriented, Rationing-free Protocol

ON QUADRATIC CORE PROJECTION PAYMENT RULES FOR COMBINATORIAL AUCTIONS YU SU THESIS

Side constraints and non-price attributes in markets

An Ascending Price Auction for Producer-Consumer Economy

Expressing Preferences with Price-Vector Agents in Combinatorial Auctions: A Brief Summary

Networks: Spring 2010 Homework 3 David Easley and Jon Kleinberg Due February 26, 2010

Auction Theory An Intrroduction into Mechanism Design. Dirk Bergemann

Computationally Feasible VCG Mechanisms. by Alpha Chau (feat. MC Bryce Wiedenbeck)

CS364B: Frontiers in Mechanism Design Lecture #17: Part I: Demand Reduction in Multi-Unit Auctions Revisited

Valuation Uncertainty and Imperfect Introspection in Second-Price Auctions

Chapter Fourteen. Topics. Game Theory. An Overview of Game Theory. Static Games. Dynamic Games. Auctions.

Auctioning Many Similar Items

Chapter 17. Auction-based spectrum markets in cognitive radio networks

Auctions. José M Vidal. Department of Computer Science and Engineering University of South Carolina. March 17, Abstract

Where are we? Knowledge Engineering Semester 2, Basic Considerations. Decision Theory

Mechanism Design and Computationally-Limited Agents. Kate Larson Computer Science Department Carnegie Mellon University

VCG in Theory and Practice

CSC304: Algorithmic Game Theory and Mechanism Design Fall 2016

Theoretical and Experimental Insights into Decentralized Combinatorial Auctions

The Ascending Bid Auction Experiment:

A Dynamic Programming Model for Determining Bidding Strategies in Sequential Auctions: Quasi-linear Utility and Budget Constraints

Robust Multi-unit Auction Protocol against False-name Bids

Notes on Introduction to Contract Theory

Fall 2004 Auction: Theory and Experiments An Outline of A Graduate Course, Johns Hopkins University.

Modelling and Solving of Multidimensional Auctions 1

Miscomputing Ratio: The Social Cost of Selfish Computing

Topics in ALGORITHMIC GAME THEORY *

distributed optimization problems, such as supply-chain procurement or bandwidth allocation. Here is an outline of this chapter. Section 3.1 considers

Bidding Clubs in First-Price Auctions Extended Abstract

Modified Truthful Greedy Mechanisms for Dynamic Virtual Machine Provisioning and Allocation in Clouds

THE PURCHASING function and the associated procurement

Synergistic Valuations and Efficiency in Spectrum Auctions

The Need for Information

An Algorithm for Multi-Unit Combinatorial Auctions

The Need for Information

Testing BOI and BOB algorithms for solving the Winner Determination Problem in Radio Spectrum Auctions

Envy Quotes and the Iterated Core-Selecting Combinatorial Auction

CS364B: Frontiers in Mechanism Design Lecture #11: Undominated Implementations and the Shrinking Auction

Domain Auction and Priority Checking Analysis

Computational Microeconomics: Game Theory, Social Choice,

Reserve Price Auctions for Heterogeneous Spectrum Sharing

A Review of the GHz Auction

Truth Revelation in Approximately Efficient Combinatorial Auctions

A Systematic Approach to Combinatorial Auction Design

Negotiating Socially Optimal Allocations of Resources: An Overview

STAMP: A Strategy-Proof Approximation Auction

HIERARCHICAL decision making problems arise naturally

Incentive-Compatible, Budget-Balanced, yet Highly Efficient Auctions for Supply Chain Formation

Interleaving Cryptography and Mechanism Design: the Case of Online Auctions. Edith Elkind Helger Lipmaa

Optimal Government Auction Design for Offshore Wind Procurement

A Note on over- and underbidding in Vickrey auctions: Do we need a new theory?

On Optimal Multidimensional Mechanism Design

38 V. Feltkamp and R. Müller limitations of computability when their rules require the solution to NP-hard optimization problems. The complexity of su

Combinatorial auctions for electronic business

Strategic bidding for multiple units in simultaneous and sequential auctions

A Modular Framework for Iterative Combinatorial Auctions

A Limitation of the Generalized Vickrey Auction in Electronic Commerce : Robustness against False-name Bids

Buy-It-Now or Snipe on ebay?

Making Waves in Wireless: Outcomes and Implications of Next Spectrum Auction

Preference Elicitation and Query Learning

First-Price Path Auctions

David Easley and Jon Kleinberg November 29, 2010

Revaluation of Bundles by Bidders in Combinatorial Auctions

Transcription:

Game Theory: Spring 2017 Ulle Endriss Institute for Logic, Language and Computation University of Amsterdam Ulle Endriss 1

Plan for Today This and the next lecture are going to be about mechanism design, which has been called inverse game theory by some. The goal is to design a game that encourages certain player behaviour. Today we are going to focus on the design of auctions: players are bidders in an auction trying to obtain certain goods we want to incentivise them to be truthful about their valuations A good starting point for finding out more about auctions is the survey by McAfee and McMillan (1987). R.P. McAfee and J. McMillan. Auctions and Bidding. Journal of Economic Literature, 25(2):699 738, 1987. Ulle Endriss 2

Auctions for a Single Item General setting for the most basic type of auction: one seller (the auctioneer) many potential buyers (the bidders) one single item to be sold: auctioneer has a reservation price (under which she won t sell) each bidder i has her own private valuation v i of the item Except for the reservation price (could be 0), we ignore the preferences of the auctioneer and regard this as a game played by the bidders. We assume quasilinear utilities. Thus, if you win the auction, then: your utility = your valuation of the item price paid for it Ulle Endriss 3

The Winner s Curse Our assumption that you just have a valuation is a simplifying one. Imagine you want to buy a house: If you want to live in the house, then it s a private-value auction and you can (maybe) be assumed to know your own valuation. If you see it as an investment, then it s a common-value auction. Your true valuation depends on the valuation of others. Winner s curse: If you win but have been uncertain about the true value of the item, should you actually be happy? Ulle Endriss 4

Auctions, Mechanisms, Games An auction is a mechanism for selling items from one seller to many potential buyers (or for one buyer to buy from many potential sellers). Think of a mechanism as a game played by the bidders (the players). The rules of the game are designed by the auctioneer, who has a particular objective in mind (e.g., to maximise revenue or to obtain truthful information from the bidders). Remark: Today we are going to avoid formal definitions of the specific mechanisms we study. They are special cases of the (formally defined) mechanisms that are going to be the subject of the next lecture. Ulle Endriss 5

Auctions Game Theory 2017 English Auctions Well-known protocol to auction off paintings, antiques, etc.: auctioneer opens by announcing her reservation price in each round, every bidder can increment the price (by > ) final bid wins Exercise: What s the best strategy to use here? Is it dominant? Ulle Endriss 6

Auctions Game Theory 2017 Dutch Auctions Dutch auctions have the advantage of being very fast: auctioneer opens by announcing an overly high initial price price is lowered a little bit in each round first bidder to accept to buy at the current price wins the auction Exercise: What s the best strategy to use here? Is it dominant? Fun Fact: Used to sell 20M flowers/day in Aalsmeer near Amsterdam. Ulle Endriss 7

Sealed-Bid Auctions Sealed-bid (as opposed to open-cry) auctions are used for awarding public building contracts and the like: each bidder submits a bid in a sealed envelope the highest bid wins (unless it s below the reservation price) This is a direct-revelation mechanism, as opposed to the indirect ones we ve seen before: bids are simply truthful or fake valuations. Exercise: What s the best strategy to use here? Is it dominant? Ulle Endriss 8

Let s Play: Sealed-Bid Auction You will receive a form indicating your true valuation for some item. All valuations have been drawn from the distribution B(100, 0.5): 30 50 70 Rules: You must play, but don t have to pay for it. If you win, you receive in game points the difference between your bid and your assigned true valuation (so if you over-bid, you might lose points). Ulle Endriss 9

Analysis It is difficult to figure out a good strategy for bidding: If you bid too low, you might lose, even if your valuation is high. If you bid too high, even if you do win, your utility will be small. Ulle Endriss 10

Dutch Auction vs. Sealed-Bid Auction The Dutch and the sealed-bid auction are strategically equivalent. As a bidder i with valuation v i, in both cases, you reason as follows: Try to estimate the highest bid ˆv of your competitors. Bid ˆv + ɛ if ˆv + ɛ < v i, i.e., in case winning would be profitable. Bid v i ɛ otherwise (just in case your estimate was wrong). In practice, there still are some differences between the two (e.g., the time pressure in a Dutch auction might affect how people bid). Ulle Endriss 11

Vickrey Auctions A Vickrey auction is a sealed-bid second-price auction: each bidder submits a bid in a sealed envelope the bidder with the highest bid wins, but pays the price of the second highest bid (unless it s below the reservation price) Exercise: What s the best strategy to use here? Is it dominant? Ulle Endriss 12

Incentive Compatibility of Vickrey Auctions A direct-revelation auction mechanism (in which you bid by submitting a valuation) is called incentive-compatible (or strategyproof ) in case submitting your true valuation is always a dominant strategy. Theorem 1 (Vickrey, 1961) Vickrey auctions are incentive-compatible. Proof: Consider bidder i with true valuation v i who is choosing between reporting v i and some fake ˆv i : Suppose v i would be a winning bid. This would be profitable for i. Then switching to ˆv i either makes no difference or results in a losing bid. Suppose some ˆv > v i would win. Then any ˆv i < ˆv would still lose, while any ˆv i ˆv would win and result in a loss in utility. William Vickrey (1914 1996) W. Vickrey. Counterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance, 16(1):8 37, 1961. Ulle Endriss 13

The Revenue Equivalence Theorem Which mechanism should the auctioneer choose? Surprisingly, in some sense and under certain assumptions, it does not matter: Theorem 2 (Vickrey, 1961) Our four auction mechanisms all give the same expected revenue, provided bidders are risk-neutral and valuations are drawn independently from the same uniform distribution. Proof sketch: expected revenue = second highest (true) valuation. Vickrey: dominant strategy is to be truthful English: bidding stops when second highest valuation is reached Dutch/ first-price sealed-bid: in expectation, bidders correctly estimate each others val s, so winner bids second highest val Remark: Above assumptions are too strong to be satisfied in practice. W. Vickrey. Counterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance, 16(1):8 37, 1961. Ulle Endriss 14

Combinatorial Auctions Selling several items through several single-item auctions in sequence is not a good idea (imagine auctioning off a left and a right shoe)... A combinatorial auction setting is a tuple N, G, v, where: N = {1,..., n} is a finite set of bidders, G = {1,..., l} is a finite set of goods, and v = (v 1,..., v n ) is a profile of (true) valuations v i : 2 G R 0. The valuations are private information. Each bidder i submits a bid by reporting a true or fake valuation ˆv i : 2 G R 0. A combinatorial auction mechanism consists of (i) an allocation rule, mapping ˆv to an association of bidders i with disjoint bundles B i G, and (ii) a pricing rule, mapping ˆv to a price vector (p 1,..., p n ) R n. The (quasilinear) utility of bidder i derived from such an outcome is: u i (B i, p i ) = v i (B i ) p i Ulle Endriss 15

Topics in Combinatorial Auctions We postpone the game-theoretical analysis of CA s to the next lecture, and briefly review some other topics of interest in this context... P. Cramton, Y. Shoham, and R. Steinberg (eds.). Combinatorial Auctions. MIT Press, 2006. Ulle Endriss 16

Aside: Bidding Languages Bidding in a CA requires reporting a valuation ˆv i : 2 G R 0, i.e., declaring a value for every possible subset of the set of goods G... In practice, bidders will only care about certain bundles of goods. Use a bidding language to encode valuations. Examples: Single-minded bids: report one bundle B i and a price p i to express ˆv i : B p i for all B B i and ˆv i : B 0 for all other bundles. Weighted formulas: report several weighted formulas (ϕ, w), with propositional variables in G, to express ˆv i : B (ϕ,w) w 1 B =ϕ More generally, the design and analysis of formal languages for the compact representation of preferences is an important research topic. N. Nisan. Bidding Languages. In P. Cramton et al. (eds.), Combinatorial Auctions. MIT Press, 2006. Y. Chevaleyre, U. Endriss, J. Lang, and N. Maudet. Preference Handling in Combinatorial Domains: From AI to Social Choice. AI Magazine, 29(4):37 46, 2008. Ulle Endriss 17

Aside: Complexity of Combinatorial Auctions Typically, the allocation rule requires us to compute an allocation that maximises utilitarian social welfare relative to the valuations reported: (B1,..., Bn) argmax ˆv i (B i ) (B 1,...,B n ) G n i N s.t. B i B j = for i j Unfortunately, this problem of Winner Determination is NP-hard, even for the case of single-minded bidders (Rothkopf et al., 1998). The proof is by reduction from Set Packing. An important research topic is to identify restrictions of the general setting of practical relevance where Winner Determination is computationally tractable. M.H. Rothkopf, A. Peke c, and R.M. Harstad. Computationally Manageable Combinational Auctions. Management Science, 44(8):1131 1147, 1998. Ulle Endriss 18

Aside: Solving Combinatorial Auctions Sometimes the kind of Winner Determination problem we face in practice is (theoretically) intractable. Yet, we still want to solve it. Designing algorithms for solving large combinatorial auction instances, for various bidding languages, is yet another important research topic. Most existing work is based on mathematical programming techniques (mixed integer programming) developed in Operations Research and heuristic-guided search techniques developed in AI. T.W. Sandholm. Optimal Winner Determination Algorithms. In P. Cramton et al. (eds.), Combinatorial Auctions. MIT Press, 2006. Ulle Endriss 19

Summary This has been an introduction to basic auction theory: four basic mechanisms: English, Dutch, FPSB, Vickrey auction Vickrey auction: simple protocol + incentive-compatible all four mechanisms generate the same expected revenue combinatorial auctions for selling bundles of goods We ve also discussed issues regarding combinatorial auctions that are not about game theory but rather about knowledge representation, complexity theory, and algorithm design. What next? Generalising Vickrey s idea to combinatorial auctions and even more general mechanisms for collectively choosing an outcome. Ulle Endriss 20