Computational Mechanism Design Chapter 3

E with self interested agents with private

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: es and every agent will receive a bundle in the provisional allocation. In fact, iBundle is provably e cient with myopic best-response agent strategies. 3.2.3 Communication Costs: Distributed Methods Shoham & Tennenholtz ST01 explore the communication complexity of computing simple functions within an auction-based algorithm i.e., with self-interested agents with private information. Essentially, the authors propose a method to compute solutions to simple functions with minimal communication complexity. Communication from the auctioneer to the agents is free in their model, while communication from agents to the auctioneer is costly. Given this, Shoham & Tennenholtz essentially provide incentive schemes so that each agent i announces its value vi by sending a single bit to the mechanism whenever the price in an auction is equal to this value. Max and min functions can be computed with a single bit from agents, and any function over n agents can be computed in n bits, which is the lower information-theoretic bound. Feigenbaum et al. FPS00 investigate cost-sharing algorithms for multicast transmission, in which a population of consumers sit on the nodes of a multicast tree. Each user has a value to receive a shared information stream, such as a lm, and each arc in the multicast tree has an associated cost. The mechanism design problem is to implement the multicast solution that maximizes total user value minus total network cost, and shares the cost across end-users. Noting that budget-balance, e ciency, and strategy-proofness are impossibility in combination the authors compare the computational properties of a Vickrey-Clarke-Groves marginal cost MC mechanism e cient and strategy-proof and a Shapley value SH mechanism budget-balanced and coalitional strategy-proof. A distributed algorithm is developed for MC, in which intermediate nodes in the tree receive messages, perform some computation, and send messages to their neighbors. The method, a bottom-up followed by a top-down traversal of the tree, computes the solution to MC with minimal communication complexity, with exactly two messages sent per link. In comparison, there is no method for the SH mechanism with e cient communication complexity. All solutions are maximal, and require as many messages per link as in a naive 80 centralized approach. Hence, communication complexity considerations lead to a strong preference for the MC mechanism, which is not budget-balanced. The study leaves many interesting open questions; e.g. are all budget-balanced solutions maximal, and what are the game-theoretic properties of alternative strategy-proof minimal mechanisms? The economic literature contains a few notable models of the e ect of limited communication and agent bounded-rationality in mechanism design, and in systems of distributed decision making and information processing. This work is relevant here, given the focus in my dissertation on computational mechanism design and in particular on the costs of complete info...
View Full Document

This document was uploaded on 03/19/2014 for the course COMP CS286r at Harvard.

Ask a homework question - tutors are online