Maximizing social welfare in congestion games via redistribution

It is well-known that efficient use of congestible resources can be achieved via marginal pricing; however, payments collected from the agents generate a budget surplus, which reduces social welfare. We show that an asymptotically first-best solution in the number of agents can be achieved by the appropriate redistribution of the budget surplus back to the agents

Combinatorial Auction-Based Pricing for Multi-tenant Autonomous Vehicle Public Transportation System

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A Shapley-value Mechanism for Bandwidth On Demand between Datacenters

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A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

Stochastic Mechanisms for Truthfulness and Budget Balance in Computational Social Choice

In this thesis, we examine stochastic techniques for overcoming game theoretic and computational issues in the collective decision making process of self-interested individuals. In particular, we examine truthful, stochastic mechanisms, for settings with a strong budget balance constraint (i.e. there is no net flow of money into or away from the agents). Building on past results in AI and computational social choice, we characterise affine-maximising social choice functions that are implementable in truthful mechanisms for the setting of heterogeneous item allocation with unit demand agents. We further provide a characterisation of affine maximisers with the strong budget balance constraint. These mechanisms reveal impossibility results and poor worst-case performance that motivates us to examine stochastic solutions. To adequately compare stochastic mechanisms, we introduce and discuss measures that capture the behaviour of stochastic mechanisms, based on techniques used in stochastic algorithm design. When applied to deterministic mechanisms, these measures correspond directly to existing deterministic measures. While these approaches have more general applicability, in this work we assess mechanisms based on overall agent utility (efficiency and social surplus ratio) as well as fairness (envy and envy-freeness). We observe that mechanisms can (and typically must) achieve truthfulness and strong budget balance using one of two techniques: labelling a subset of agents as ``auctioneers'' who cannot affect the outcome, but collect any surplus; and partitioning agents into disjoint groups, such that each partition solves a subproblem of the overall decision making process. Worst-case analysis of random-auctioneer and random-partition stochastic mechanisms show large improvements over deterministic mechanisms for heterogeneous item allocation. In addition to this allocation problem, we apply our techniques to envy-freeness in the room assignment-rent division problem, for which no truthful deterministic mechanism is possible. We show how stochastic mechanisms give an improved probability of envy-freeness and low expected level of envy for a truthful mechanism. The random-auctioneer technique also improves the worst-case performance of the public good (or public project) problem. Communication and computational complexity are two other important concerns of computational social choice. Both the random-auctioneer and random-partition approaches offer a flexible trade-off between low complexity of the mechanism, and high overall outcome quality measured, for example, by total agent utility. They enable truthful and feasible solutions to be incrementally improved on as the mechanism receives more information and is allowed more processing time. The majority of our results are based on optimising worst-case performance, since this provides guarantees on how a mechanism will perform, regardless of the agents that use it. To complement these results, we perform empirical, average-case analyses on our mechanisms. Finally, while strong budget balance is a fixed constraint in our particular social choice problems, we show empirically that this can improve the overall utility of agents compared to a utility-maximising assignment that requires a budget imbalanced mechanism

Essays in Economic Theory

This thesis consists of five chapters on topics in mechanism design and voting. In Chapter 1, we study a committee deciding collectively whether to accept a given proposal or to maintain the status quo. Committee members are privately informed about their valuations and monetary transfers are possible. According to which rule should the committee make its decision? We consider strategy-proof and anonymous social choice functions and solve for the decision rule that maximizes utilitarian welfare, which takes monetary transfers to an external agency explicitly into account. For regular distributions of preferences, we find that it is optimal to exclude monetary transfers and to decide by qualified majority voting. This sheds new light on the common objection that criticizes voting for its inefficiency. In Chapter 2, we study welfare-optimal decision rules for committees that repeatedly take a binary decision. Committee members are privately informed about their payoffs and monetary transfers are not feasible. In static environments, the only strategy-proof mechanisms are voting rules which are inefficient as they do not condition on preference intensities. The dynamic structure of repeated decision-making allows for richer decision rules that overcome this inefficiency. Nonetheless, we show that often simple voting is optimal for two-person committees. This holds for many prior type distributions and irrespective of the agents' patience. In Chapter 3, we study binary, sequential voting procedures in settings with privately informed agents and single-peaked (or single-crossing) preferences. We identify two conditions on binary voting trees, convexity of divisions and monotonicity of qualified majorities, ensuring that sincere voting at each stage forms an ex-post perfect equilibrium in the associated extensive form game with incomplete information. We illustrate our findings with several case studies: procedures that do not satisfy our two conditions offer ample space for strategic manipulations. Conversely, when the agenda satisfied our conditions, sincere behavior was indeed the most likely outcome. In Chapter 4, we study how a principal should optimally choose between implementing a new policy and keeping status quo when the information relevant for the decision is privately held by agents. Agents are strategic in revealing their information, but the principal can verify an agent's information at a given cost. We exclude monetary transfers. When is it worthwhile for the principal to incur the cost and learn an agent's information? We characterize the mechanism that maximizes the expected utility of the principal. This mechanism can be implemented as a weighted majority voting rule, where agents are given additional weight if they provide evidence about their information. The evidence is verified whenever it is decisive for the principal's decision. Additionally, we find a general equivalence between Bayesian and ex-post incentive compatible mechanisms in this setting. In Chapter 5, we are interested in strategy-proof mechanisms that maximize the agents' residual surplus, that is, the utility derived from the physical allocation minus transfers accruing to an external entity, in an independent private value auction environment. We find that, under the assumption of an increasing hazard rate of type distributions, an optimal deterministic mechanism never extracts any net payments from the agents, that is, it will be budget-balanced. Specifically, optimal mechanisms have a simple "posted price'' or "option'' form. In the bilateral trade environment, we obtain optimality of posted price mechanisms without any assumption on type distributions

Essays on contract theory and organizational economics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 2009."September 2009." Cataloged from PDF version of thesis.Includes bibliographical references.Chapter 1 develops a non-parametric methodology for identifying contract optimality in the presence of moral hazard. Following the first order approach, a standard method of computing optimal contracts, the paper first proves two theoretical properties of the solutions to the moral hazard problem. First, we show that the profit loss (relative to the optimal contract) for given effort level has a unique lower bound. The second property is an equivalence between the first order condition (Mirrlees-Holmstrom Condition) and the Cramer-Rao Lower Bound (CRLB). These two properties provide the foundations for (1) identifying optimality, and (2) performing statistical inference on the agent's primitives based on an observed sequence of pairs of outputs and payments. The paper shows that under some weak conditions, contract optimality is identified, as long as the output generating process is additive in effort and noise. Identification does not require the agent's effort to be observed by the principal or the econometrician, and requires no knowledge of (1) the details of the contract, (2) the agent's cost of effort, (3) the agent's monetary utility, or (4) the distribution of output. Based on the approach proposed in this paper, we test contract optimality for a piece-rate contract, and estimate bounds on the profit loss for cotton weavers in Zhejiang Province, China. Chapter 2 develops a new method to justify the validity of the first order approach (FOA). We first prove that checking the validity amounts to checking the existence of a fixed point of the agent's best response against a Mirrlees-Holmstrom (MH) class contract offered by the principal, given some specifications of complemetary conditions.(cont.) The main advantage of the current approach is the relaxation of the global concavity of agent utility. We show that under a set of mild conditions, the fixed point approach is applicable and the solution to the principal agent problem exists. In particular, if the log likelihood ratio is monotonically increasing in output but decreasing in effort, the best response correspondence against a MK contract has and only has one unique fixed point. Our approach unifies Jewitt's (1988) and Rogerson's (1985) proofs of validity of FOA, and provides a general method to judge validity of FOA. Based on the fixed-point approach, with some additional specifications, we restore Jewitt's (1988) results to situations where the distribution is not convex and the log likelihood ratio is not bounded from below (e.g., normal distribution), or there exists a limited liability constraint. Furthermore, we generalize our results to a situation where the agent's utility is non separable. In this fairly general environment, we prove a necessary and sufficient condition for the FOA to be valid, which provides an important method to identify the validity of FOA and compute the solution of the original problem. Finally, we provide a necessary and sufficient condition for a general non-linear bi-level optimization problem to be solvable based on FOA, without a convex constrained set. Chapter 3 constructs a concrete mechanism/auction to explore the consequence of imposing the ex post participation constraint.(cont.) The main findings are: (1) In private good cases (symmetric or asymmetric), we can obtain ex post first best, ex post budget balance, at least interim incentive compatibility and ex post individual rationality (we call it ex post social efficiency), whenever the VCG mechanism runs expected surplus. And the mechanism generating an ex post monotonic payoff is generically unique (up to an ex ante side-pay). In addition, compared with standard auctions, our mechanism generates a risk-free revenue to the seller and ex post invidually rational payoff to the bidders. (2) In a general preference case with externality, we show there exists an ex post socially efficient mechanism when the number of participants is sufficiently small (n = 2). And the choice of mechanism depends on whether the quantity is endogenous or not. (3) As an implication, we provide a general discussion on how divisibility, endowment distribution and preference affect the possibility of trade. For the negative result, we show a set of conditions for non-existence of an ex post socially efficient trade, such as either utility is linear or the lowest type agent's utility is independent of his endowment, which can be regarded as stronger version of no-trade theorem (Myerson-Satterthwaite, 1983). This proposition implies non-existence of an ex post socially efficient partner dissolving mechanism. For the positive side, we provide a sufficient condition for existence of ex post socially efficient trade mechanism and show an explicit example. JEL Code: D86 D81 C12 D82by Rongzhu Ke.Ph.D

Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces