Theodore Groves

Bio: Theodore Groves is an academic researcher from Northwestern University. The author has contributed to research in topics: Incentive compatibility & Max-min fairness. The author has an hindex of 5, co-authored 6 publications receiving 3304 citations.

Incentives in Teams

Abstract: This paper analyzes the problem of inducing the members of an organization to behave as if they formed a team. Considered is a conglomerate-type organization consisting of a set of semi-autonomous subunits that are coordinated by the organization's head. The head's incentive problem is to choose a set of employee compensation rules that will induce his subunit managers to communicate accurate information and take optimal decisions. The main result exhibits a particular set of compensation rules, an optimal incentive structure, that leads to team behavior. Particular attention is directed to the informational aspects of the problem. An extended example of a resource allocation model is discussed and the optimal incentive structure is interpreted in terms of prices charged by the head for resources allocated to the subunits.

Some limitations of demand revelaing processes

Abstract: The proposition that, due to the free-rider phenomenon, there is no decentralized mechanism yielding a Pareto-optimal allocation of resources in the presence of public goods has recently been challenged by Clarke (!971), Groves and Loeb (1975), Groves and Ledyard (1977), and Tideman and Tullock (1976) among others. It is now believed by some that, through the use of "demand-revealing mechanisms", allocations can be achieved which are efficient or, at the very least, superior to those arrived at by markets or other means. While we agree that these mechanisms are potential candidates for implementation, we feel that there are a number of limitations which they suffer which must be seriously considered before one is adopted in practice. In this paper, we present five warnings intended to dampen any premature urge to adopt a constitutional amendment to institute one of these demand-revealing mechanisms. To coherently discuss the various limitations, we briefly survey (in Sections 3 7) the state of knowledge about these mechanisms, in the context o f a simple model. We then present five specific properties of these mechanisms (Sections 811) which could l~inder successfd implementation. These potential problems are summarized in the next section. We conclude this paper with a brief discussion (Section 12) of some progress made in overcombing a few of these difficulties.

Incentive Compatible Control of Decentralized Organizations

Abstract: Many organizational decision problems may be usefully modeled as the programming problem: $${\text{P}}:\,\,\,\,\mathop {{\text{Max}}}\limits_{\text{x}} {\text{F}}\left( {\text{x}} \right)$$ (1.1) subject to G(x) ≤ 0 where x ∈ ℝN, F: ℝN→ℝ, and G : ℝN→ℝK.

The Theory of Incentives: The Principal-Agent Model

Abstract: Economics has much to do with incentives--not least, incentives to work hard, to produce quality products, to study, to invest, and to save. Although Adam Smith amply confirmed this more than two hundred years ago in his analysis of sharecropping contracts, only in recent decades has a theory begun to emerge to place the topic at the heart of economic thinking. In this book, Jean-Jacques Laffont and David Martimort present the most thorough yet accessible introduction to incentives theory to date. Central to this theory is a simple question as pivotal to modern-day management as it is to economics research: What makes people act in a particular way in an economic or business situation? In seeking an answer, the authors provide the methodological tools to design institutions that can ensure good incentives for economic agents. This book focuses on the principal-agent model, the "simple" situation where a principal, or company, delegates a task to a single agent through a contract--the essence of management and contract theory. How does the owner or manager of a firm align the objectives of its various members to maximize profits? Following a brief historical overview showing how the problem of incentives has come to the fore in the past two centuries, the authors devote the bulk of their work to exploring principal-agent models and various extensions thereof in light of three types of information problems: adverse selection, moral hazard, and non-verifiability. Offering an unprecedented look at a subject vital to industrial organization, labor economics, and behavioral economics, this book is set to become the definitive resource for students, researchers, and others who might find themselves pondering what contracts, and the incentives they embody, are really all about.

Smart Grid — The New and Improved Power Grid: A Survey

Abstract: The Smart Grid, regarded as the next generation power grid, uses two-way flows of electricity and information to create a widely distributed automated energy delivery network. In this article, we survey the literature till 2011 on the enabling technologies for the Smart Grid. We explore three major systems, namely the smart infrastructure system, the smart management system, and the smart protection system. We also propose possible future directions in each system. colorred{Specifically, for the smart infrastructure system, we explore the smart energy subsystem, the smart information subsystem, and the smart communication subsystem.} For the smart management system, we explore various management objectives, such as improving energy efficiency, profiling demand, maximizing utility, reducing cost, and controlling emission. We also explore various management methods to achieve these objectives. For the smart protection system, we explore various failure protection mechanisms which improve the reliability of the Smart Grid, and explore the security and privacy issues in the Smart Grid.

Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations

Abstract: This exciting and pioneering new overview of multiagent systems, which are online systems composed of multiple interacting intelligent agents, i.e., online trading, offers a newly seen computer science perspective on multiagent systems, while integrating ideas from operations research, game theory, economics, logic, and even philosophy and linguistics. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming. Written by two of the leading researchers of this engaging field, this book will surely serve as THE reference for researchers in the fastest-growing area of computer science, and be used as a text for advanced undergraduate or graduate courses.

Algorithmic Game Theory

Abstract: A new era of theoretical computer science addresses fundamental problems about auctions, networks, and human behavior.