Incentives and Information in Multiagent Settings

Incentives and Information in Multiagent Settings PDF Author: Omar Ahmed Nayeem
Publisher:
ISBN:
Category :
Languages : en
Pages : 334

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Book Description
This dissertation comprises three papers, each of which analyzes a mechanism design issue that arises in a setting with multiple agents that need to either acquire or aggregate information for use in a decision. The decision affects all agents as well as a principal, who also plays the role of mechanism designer. The theoretical models that I develop in these papers can be applied to a wide range of diverse settings, but I emphasize applications in the areas of organizational economics and political economics. The first paper, titled ``The Value of `Useless' Bosses, '' presents a novel view of the role of middle managers in organizations. Conventional wisdom regarding middle management suggests that a principal that can administer her organization independently has no reason to hire a manager, and that a principal that can benefit from a manager's services should hire one with aligned interests. The paper highlights a channel through which virtually any principal can benefit from the services of a manager, particularly of one whose interests differ. Specifically, when a principal relies on a worker to acquire information for an organizational decision, she can strengthen the worker's incentives by delegating the decision to a ``biased'' manager. Although casual observation of the game suggests that the manager's position is redundant, delegation benefits the principal. Thus, the paper helps to reconcile the prevalence of middle management with its widespread lamentation. It also illustrates how discord between a manager and a worker can improve an organization's performance. The results are consistent with outcomes from various knowledge-based organizations. The second paper, titled ``Communication and Preference (Mis)alignment in Organizations, '' conveys insights that are similar to the ones from ``The Value of `Useless' Bosses.'' Like the previous paper, this one explains the benefits of biased agents (both workers and managers) in organizations. However, unlike the previous paper, this one assumes that an organization's principal--whose time, technical expertise, and attention are limited--relies upon division managers to produce reports, which summarize information acquired by workers, to inform her decisions. Given this assumption, a pressing question for the principal is not whether to appoint a manager, but rather which type of manager to appoint. Note that two types of agency problems can arise in the setting described above. First, workers that bear private costs for their information acquisition efforts may not exert as much effort as the principal would like. Second, managers that do not share the principal's preferences over decisions can produce false reports. The paper shows that, although preference alignment within the organization may be expected to minimize the principal's losses from agency, the principal may benefit from intraorganizational conflict. In particular, the principal can use a manager's bias to strengthen a worker's incentives to acquire information. Since a manager's incentive to mislead the principal vanishes if the acquired information is of sufficiently high quality, the principal realizes an unambiguous welfare gain by hiring a biased manager. The principal can further enhance her welfare by also hiring a biased worker, whose bias clashes with the manager's. The third paper, titled ``Efficient Electorates, '' analyzes a social choice setting with pure common values, private noisy information about an unobservable payoff-relevant state of the world, and costless voting. In such a setting, an economic argument in favor of direct democracy is essentially one about information aggregation: if all citizens vote according to their private information--which, on average, is correct--then, in large majority-rule elections, the probability that the welfare-maximizing outcome is implemented is close to one. This argument, formalized first by the Marquis de Condorcet in his celebrated ``jury theorem'' and later extended to cover more general environments, is an asymptotic result that requires voters' information to be sufficiently uncorrelated. The paper shows that, for a fixed number of sincere voters with shared information sources, direct democracy is often suboptimal. It then considers the problem of appointing an optimal electorate given the allocation of information. In special cases of this framework, the problem can be viewed as the choice of an electorate from a set of individuals that communicate with each other via a social network before the election. It provides a characterization of the optimal electorate for certain classes of networks. Because the optimal electorate is often a proper subset of the full set of agents, representative democracy--even in the absence of voting costs--is often more efficient than direct democracy. As the paper illustrates through various examples, though, the solution to the problem of optimal elector appointment is unstable, and so a general characterization of the optimal electorate is elusive.

Incentives and Information in Multiagent Settings

Incentives and Information in Multiagent Settings PDF Author: Omar Ahmed Nayeem
Publisher:
ISBN:
Category :
Languages : en
Pages : 334

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Book Description
This dissertation comprises three papers, each of which analyzes a mechanism design issue that arises in a setting with multiple agents that need to either acquire or aggregate information for use in a decision. The decision affects all agents as well as a principal, who also plays the role of mechanism designer. The theoretical models that I develop in these papers can be applied to a wide range of diverse settings, but I emphasize applications in the areas of organizational economics and political economics. The first paper, titled ``The Value of `Useless' Bosses, '' presents a novel view of the role of middle managers in organizations. Conventional wisdom regarding middle management suggests that a principal that can administer her organization independently has no reason to hire a manager, and that a principal that can benefit from a manager's services should hire one with aligned interests. The paper highlights a channel through which virtually any principal can benefit from the services of a manager, particularly of one whose interests differ. Specifically, when a principal relies on a worker to acquire information for an organizational decision, she can strengthen the worker's incentives by delegating the decision to a ``biased'' manager. Although casual observation of the game suggests that the manager's position is redundant, delegation benefits the principal. Thus, the paper helps to reconcile the prevalence of middle management with its widespread lamentation. It also illustrates how discord between a manager and a worker can improve an organization's performance. The results are consistent with outcomes from various knowledge-based organizations. The second paper, titled ``Communication and Preference (Mis)alignment in Organizations, '' conveys insights that are similar to the ones from ``The Value of `Useless' Bosses.'' Like the previous paper, this one explains the benefits of biased agents (both workers and managers) in organizations. However, unlike the previous paper, this one assumes that an organization's principal--whose time, technical expertise, and attention are limited--relies upon division managers to produce reports, which summarize information acquired by workers, to inform her decisions. Given this assumption, a pressing question for the principal is not whether to appoint a manager, but rather which type of manager to appoint. Note that two types of agency problems can arise in the setting described above. First, workers that bear private costs for their information acquisition efforts may not exert as much effort as the principal would like. Second, managers that do not share the principal's preferences over decisions can produce false reports. The paper shows that, although preference alignment within the organization may be expected to minimize the principal's losses from agency, the principal may benefit from intraorganizational conflict. In particular, the principal can use a manager's bias to strengthen a worker's incentives to acquire information. Since a manager's incentive to mislead the principal vanishes if the acquired information is of sufficiently high quality, the principal realizes an unambiguous welfare gain by hiring a biased manager. The principal can further enhance her welfare by also hiring a biased worker, whose bias clashes with the manager's. The third paper, titled ``Efficient Electorates, '' analyzes a social choice setting with pure common values, private noisy information about an unobservable payoff-relevant state of the world, and costless voting. In such a setting, an economic argument in favor of direct democracy is essentially one about information aggregation: if all citizens vote according to their private information--which, on average, is correct--then, in large majority-rule elections, the probability that the welfare-maximizing outcome is implemented is close to one. This argument, formalized first by the Marquis de Condorcet in his celebrated ``jury theorem'' and later extended to cover more general environments, is an asymptotic result that requires voters' information to be sufficiently uncorrelated. The paper shows that, for a fixed number of sincere voters with shared information sources, direct democracy is often suboptimal. It then considers the problem of appointing an optimal electorate given the allocation of information. In special cases of this framework, the problem can be viewed as the choice of an electorate from a set of individuals that communicate with each other via a social network before the election. It provides a characterization of the optimal electorate for certain classes of networks. Because the optimal electorate is often a proper subset of the full set of agents, representative democracy--even in the absence of voting costs--is often more efficient than direct democracy. As the paper illustrates through various examples, though, the solution to the problem of optimal elector appointment is unstable, and so a general characterization of the optimal electorate is elusive.

Incentive Plans and Multi-agent Information Sharing

Incentive Plans and Multi-agent Information Sharing PDF Author: Susan Pickard Ravenscroft
Publisher:
ISBN:
Category : Bonuses (Employee fringe benefits)
Languages : en
Pages : 356

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Book Description


Multiagent Incentive Contracts

Multiagent Incentive Contracts PDF Author: Qi Luo
Publisher:
ISBN:
Category :
Languages : en
Pages : 17

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Book Description
Incentive contracts with multiple agents is a classical decentralized decision-making problem with asymmetric information. Contract design aims to incentivize noncooperative agents to act in the principal's interest over a planning horizon. We extend the single-agent incentive contract to a multiagent setting with history-dependent terminal conditions. Our contributions include: (a) Finding sufficient conditions for the existence of optimal multiagent incentive contracts and conditions under which they form a unique Nash Equilibrium; (b) Showing that the optimal multiagent incentive contracts can be solved by a Hamilton-Jacobi-Bellman (HJB) equation with equilibrium constraints; (c) Proposing a backward iterative algorithm to solve the problem.

The Theory of Incentives

The Theory of Incentives PDF Author: Jean-Jacques Laffont
Publisher: Princeton University Press
ISBN: 1400829453
Category : Business & Economics
Languages : en
Pages : 436

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Book Description
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.

Incentives in One-sided Matching Problems with Ordinal Preferences

Incentives in One-sided Matching Problems with Ordinal Preferences PDF Author: Hadi Hosseini
Publisher:
ISBN:
Category :
Languages : en
Pages : 179

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Book Description
One of the core problems in multiagent systems is how to efficiently allocate a set of indivisible resources to a group of self-interested agents that compete over scarce and limited alternatives. In these settings, mechanism design approaches such as matching mechanisms and auctions are often applied to guarantee fairness and efficiency while preventing agents from manipulating the outcomes. In many multiagent resource allocation problems, the use of monetary transfers or explicit markets are forbidden because of ethical or legal issues. One-sided matching mechanisms exploit various randomization and algorithmic techniques to satisfy certain desirable properties, while incentivizing self-interested agents to report their private preferences truthfully. In the first part of this thesis, we focus on deterministic and randomized matching mechanisms in one-shot settings. We investigate the class of deterministic matching mechanisms when there is a quota to be fulfilled. Building on past results in artificial intelligence and economics, we show that when preferences are lexicographic, serial dictatorship mechanisms (and their sequential dictatorship counterparts) characterize the set of all possible matching mechanisms with desirable economic properties, enabling social planners to remedy the inherent unfairness in deterministic allocation mechanisms by assigning quotas according to some fairness criteria (such as seniority or priority). Extending the quota mechanisms to randomized settings, we show that this class of mechanisms are envyfree, strategyproof, and ex post efficient for any number of agents and objects and any quota system, proving that the well-studied Random Serial Dictatorship (RSD) is also envyfree in this domain. The next contribution of this thesis is providing a systemic empirical study of the two widely adopted randomized mechanisms, namely Random Serial Dictatorship (RSD) and the Probabilistic Serial Rule (PS). We investigate various properties of these two mechanisms such as efficiency, strategyproofness, and envyfreeness under various preference assumptions (e.g. general ordinal preferences, lexicographic preferences, and risk attitudes). The empirical findings in this thesis complement the theoretical guarantees of matching mechanisms, shedding light on practical implications of deploying each of the given mechanisms. In the second part of this thesis, we address the issues of designing truthful matching mechanisms in dynamic settings. Many multiagent domains require reasoning over time and are inherently dynamic rather than static. We initiate the study of matching problems where agents' private preferences evolve stochastically over time, and decisions have to be made in each period. To adequately evaluate the quality of outcomes in dynamic settings, we propose a generic stochastic decision process and show that, in contrast to static settings, traditional mechanisms are easily manipulable. We introduce a number of properties that we argue are important for matching mechanisms in dynamic settings and propose a new mechanism that maintains a history of pairwise interactions between agents, and adapts the priority orderings of agents in each period based on this history. We show that our mechanism is globally strategyproof in certain settings (e.g. when there are 2 agents or when the planning horizon is bounded), and even when the mechanism is manipulable, the manipulative actions taken by an agent will often result in a Pareto improvement in general. Thus, we make the argument that while manipulative behavior may still be unavoidable, it is not necessarily at the cost to other agents. To circumvent the issues of incentive design in dynamic settings, we formulate the dynamic matching problem as a Multiagent MDP where agents have particular underlying utility functions (e.g. linear positional utility functions), and show that the impossibility results still exist in this restricted setting. Nevertheless, we introduce a few classes of problems with restricted preference dynamics for which positive results exist. Finally, we propose an algorithmic solution for agents with single-minded preferences that satisfies strategyproofness, Pareto efficiency, and weak non-bossiness in one-shot settings, and show that even though this mechanism is manipulable in dynamic settings, any unilateral deviation would benefit all participating agents.

PRIMA 2022: Principles and Practice of Multi-Agent Systems

PRIMA 2022: Principles and Practice of Multi-Agent Systems PDF Author: Reyhan Aydoğan
Publisher: Springer Nature
ISBN: 3031212037
Category : Computers
Languages : en
Pages : 714

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Book Description
This book constitutes the refereed proceedings of the 23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, held in hybrid mode in Valencia, Spain, in November 2022. The 31 full papers presented together with 15 short papers and 1 demo paper were carefully reviewed and selected from 100 submissions. The conference covers a wide range of ranging from foundations of agent theory and engineering aspects of agent systems, to emerging interdisciplinary areas of agent-based research.

Multi-Agent Systems

Multi-Agent Systems PDF Author: Ariel Rosenfeld
Publisher: Springer Nature
ISBN: 3030822540
Category : Computers
Languages : en
Pages : 292

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Book Description
This book constitutes the revised post-conference proceedings of the 18th European Conference on Multi-Agent Systems, EUMAS 2021. The conference was held online in June, 2021. 16 full papers are presented in this volume, each of which carefully reviewed and selected from a total of 51 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of multi-agent systems.

Multiagent System Technologies

Multiagent System Technologies PDF Author: Jürgen Dix
Publisher: Springer
ISBN: 3642161782
Category : Computers
Languages : en
Pages : 233

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Book Description
Annotation. This book constitutes the proceedings of the 8th German Conference on Multiagent System Technologies held in Leipzig, Germany, in September 2010.

Research Handbook on Accounting and Information Systems

Research Handbook on Accounting and Information Systems PDF Author: Julia A. Smith
Publisher: Edward Elgar Publishing
ISBN: 1802200622
Category : Business & Economics
Languages : en
Pages : 335

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Book Description
The role of the accountant is changing, as developments in technology alter the ways in which information is prepared and analysed. This Research Handbook addresses the use of both financial and non-financial information for planning, decision-making and control in organisations. Written by experts in the field, the book uses comprehensive literature reviews, empirical fieldwork and theoretical developments to provide an overview of research in this important area.

Game Theory for Data Science

Game Theory for Data Science PDF Author: Boi Mirsky
Publisher: Springer Nature
ISBN: 3031015770
Category : Computers
Languages : en
Pages : 135

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Book Description
Intelligent systems often depend on data provided by information agents, for example, sensor data or crowdsourced human computation. Providing accurate and relevant data requires costly effort that agents may not always be willing to provide. Thus, it becomes important not only to verify the correctness of data, but also to provide incentives so that agents that provide high-quality data are rewarded while those that do not are discouraged by low rewards. We cover different settings and the assumptions they admit, including sensing, human computation, peer grading, reviews, and predictions. We survey different incentive mechanisms, including proper scoring rules, prediction markets and peer prediction, Bayesian Truth Serum, Peer Truth Serum, Correlated Agreement, and the settings where each of them would be suitable. As an alternative, we also consider reputation mechanisms. We complement the game-theoretic analysis with practical examples of applications in prediction platforms, community sensing, and peer grading.