This research advances distributed information sharing by equipping nodes (e.g., software agents) in a distributed network with (1) partner selection algorithms in cooperative environments, and (2) strategies for providing and requesting information in competitive environments. In cooperative environments, information providers are willing to provide requested information, but information consumers must consider uncertainty in the quality of provided information when selecting appropriate information providers. In competitive environments, if a self-interested agent can be an information consumer and provider at the same time, agents need to determine the best ways to request and provide information so that the information acquisition utility can be maximized. This research defines a set of metrics for evaluating information acquisition utility, and presents a game-theoretic approach for determining the best information sharing strategies based on stochastic games. The results show how agents build collaborative relationships with appropriate agents and how the information acquisition utility is affected by those relationships. / text

<p>By purposefully utilising sensors, for instance by a datafusion system, the state of some system-relevant environmentmight be adequately assessed to support decision-making. Theever increasing access to sensors o.ers great opportunities,but alsoincurs grave challenges. As a result of managingmultiple sensors one can, e.g., expect to achieve a morecomprehensive, resolved, certain and more frequently updatedassessment of the environment than would be possible otherwise.Challenges include data association, treatment of con.ictinginformation and strategies for sensor coordination.</p><p>We use the term information acquisition to denote the skillof a data fusion system to actively acquire information. Theaim of this thesis is to instructively situate that skill in ageneral context, explore and classify related research, andhighlight key issues and possible future work. It is our hopethat this thesis will facilitate communication, understandingand future e.orts for information acquisition.</p><p>The previously mentioned trend towards utilisation of largesets of sensors makes us especially interested in large-scaleinformation acquisition, i.e., acquisition using many andpossibly spatially distributed and heterogeneous sensors.</p><p>Information acquisition is a general concept that emerges inmany di.erent .elds of research. In this thesis, we surveyliterature from, e.g., agent theory, robotics and sensormanagement. We, furthermore, suggest a taxonomy of theliterature that highlights relevant aspects of informationacquisition.</p><p>We describe a function, perception management (akin tosensor management), which realizes information acquisition inthe data fusion process and pertinent properties of itsexternal stimuli, sensing resources, and systemenvironment.</p><p>An example of perception management is also presented. Thetask is that of managing a set of mobile sensors that jointlytrack some mobile targets. The game theoretic algorithmsuggested for distributing the targets among the sensors proveto be more robust to sensor failure than a measurement accuracyoptimal reference algorithm.</p><p><b>Keywords:</b>information acquisition, sensor management,resource management, information fusion, data fusion,perception management, game theory, target tracking</p>

Thesis advisor: Rebecca Lownhaupt / This qualitative case study examined the role of the principal in organizational learning in one small, urban school district. The study focused on ways in which building leaders acquired, interpreted, and distributed information in schools, and how these practices were monitored. Findings from analysis of principal interviews and document review showed that monthly meetings with the superintendent served as the primary source of information gathered by principals, while meetings with their peers provided a vehicle for interpreting information shared. Within their buildings, principals used various building-level meetings, written communication, and the teacher evaluation processes as vehicles for information distribution to staff. Meetings and observation of practice were utilized to monitor efficacy of their distribution practices. Findings suggested that principals did not identify themselves as the primary keepers or distributors of information as it pertained to teaching and learning. Using a distributed approach, they instead relied on district directors and instructional coaches for that aspect of the work. / Thesis (EdD) — Boston College, 2016. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Leadership and Higher Education.

This dissertation consists of three essays. Essay 1: Lobbying, Information, and Private and Social Welfare. Lobbying is potentially welfare improving if it is a form of information transmission. This essay studies when and for whom this is the case. In the model, a government (G) can redistribute income between two interest groups (A and B). Only one of them (A) has the opportunity to lobby. Lobbying is understood as A’s acquiring and strategically revealing policy-relevant information to G. Among the results is that A may be worse off as a consequence of lobbying while B is better off. It can also be the case that lobbying makes both the active and passive interest groups and the government all worse off. Essay 2: Are we better off if our politicians know how the economy works? This essay concerns public policy and welfare in a society where citizens’ preferences over public policy depend, in varying degrees, on some unknown state of the world. That is, people are heterogeneous with respect to their responsiveness to the unknown state. Public policy is decided on by a policymaker who is elected among the citizens by majority vote. Given this framework it is asked whether the citizens would be better off if the amount of uncertainty that the policymaker is facing were smaller. Among the results is that those who are sufficiently responsive to the unknown state may be worse off if the variance of the stochastic variable decreases. Essay 3: Incomplete information in the Samaritan’s dilemma: The dilemma (almost) vanishes. Suppose that an altruistic person, A, is willing to transfer resources to a second person, B, if B comes upon hard times. If B anticipates that A will act in this manner, B will save "too little" from both agents’ point of view. This is the Samaritan’s dilemma. The mechanism in the dilemma has been employed in an extensive literature, addressing a wide range of both normative and positive issues. However, this essay shows that the undersaving result is not robust to the assumption that information is complete: by adding an arbitrarily small amount of uncertainty one can sustain an equilibrium outcome that is arbitrarily close to ex post incentive efficiency. One may also sustain outcomes with oversaving. / Diss. Stockholm : Handelshögsk., 1998

<p>This dissertation consists of two chapters studying monetary and fiscal policy. In the first chapter, I study the welfare benefits and costs of increased central bank transparency in a dynamic model of costly information acquisition where agents can either choose to gather new costly information or remember information from the past for free. Information is costly to acquire due to an agent's limited attention. Agents face an intratemporal decision on how to allocate attention across public and private signals within the period and an intertemporal decision on how to allocate attention over time. The model embeds a coordination externality into the dynamic framework which motivates agents to be overly attentive to public information and creates the possibility of costly transparency. Interestingly, allowing for intratemporal and intertempral tradeoffs for attention amplifies (attenuates) the benefits (costs) of earlier transparency whereas it attenuates (amplifies) the benefits (costs) of delayed transparency. </p><p>The second chapter, co-authored with Barbara Rossi and Atsushi Inoue, studies the empirical effects of unexpected changes in government spending and tax policy on heterogeneous agents. We use data from the Consumption Expenditure Survey (CEX) to estimate individual-level impulse responses as well as multipliers for government spending and tax policy shocks. The main empirical finding of this paper is that unexpected fiscal shocks have substantially different effects on consumers depending on their age, income levels, and education. In particular, the wealthiest individuals tend to behave according to the predictions of standard RBC models, whereas the poorest individuals tend to behave according to standard IS-LM (non-Ricardian) models, due to credit constraints. Furthermore, government spending policy shocks tend to decrease consumption inequality, whereas tax policy shocks most negatively affect the lives of the poor, more so than the rich, thus increasing consumption inequality.</p> / Dissertation

Increasingly, predictive models are used to support routine business de- cisions and are integral to the strategic competitive business strategies for a wide range of industries. Most often, data-driven predictive models are in- duced from training data obtained through the businesss routine operations. However, recent research on policies for intelligent information acquisitions suggests that proactive acquisition of information can improve models at a lower cost. Most active information acquisition policies are accuracy centric; they aim to identify acquisitions of training data that are particularly benefi- cial for improving the predictive accuracy of a given model. In practice, however, inferences from a predictive model are often used along with inferences from other predictive models as well as constant factors to inform arbitrarily complex decisions. In this dissertation, I discuss how these settings motivate a new kind of collaborative information acquisition (CIA) policies that exploit knowledge of the decision to allow multiple predictive models to collaboratively prioritize the prospective information acquisitions, so as to best improve the decisions they inform jointly. I present a framework for CIA policies and two specific CIA policies: CIA for binary decisions (CIA-BD), and CIA for top-ranked opportu- nities in terms of expected revenue (CIA-TR). Extensive empirical evaluations of the policies on real-world data suggest that the notion of CIA policies is indeed a valuable one. In particular, I demonstrate that these two new poli- cies lead to superior decision-making performances as compared to those of alternative policies that are either decision-centric or do not allow multiple models to collaboratively prioritize acquisitions. The performance exhibited by the CIA policies suggest that these policies are able to effectively exploit knowledge of the decisions to avoid greedy improvements in accuracy of any individual model informing the decisions; instead, they promote improvements in any one or all of the models when such improvements are likely to benefit the decisions. / text

This dissertation addresses the economic behavior and political influence activities by lobbyists today by examining the existence, mechanisms, and welfare implications of commercial lobbying activities and their optimal regulation. In the second chapter of this dissertation, a novel model of lobbying is presented that explains the behavior of commercial lobbying firms (such as the so-called K-Street lobbyists of Washington, D.C.). In contrast to classical special interest groups, commercial lobbying firms represent a variety of clients and are not directly affected by policy outcomes. They are hired by citizens to advocate policy proposals to politicians that are beneficial to the citizens but also have social implications. Using a model with a market for lobbying services and agency relationships between lobbyists and policymakers it can be shown why commercial lobbying firms exist. It can also be shown that self-interested policymakers, who observe lobbying activities, may employ commercial lobbying firms in a socially inefficient manner. In the third chapter of this dissertation, the analysis examines the effective regulation of commercial lobbying activities and focuses on the endogenous choice of regulatory institutions. The analysis uses the model of commercial lobbying presented in the second chapter. I derive the institutional conditions under which a market outcome can be first-best as well as the conditions under which a first-best institution will be self-stable. One result is that current regulations may fail to be effective and cannot limit lobbyists' and policymakers' incentives to substitute financial contributions for the socially beneficial acquisition of information. Additional results explain why endogenous reforms may or may not occur. In the fourth chapter of this dissertation, the analysis uses a dynamic model of commercial lobbying with lobbyists who undertake unobservable investigation efforts and promise financial contributions. It is shown that repeated relationships with lobbyists simplify a policymaker's information and contracting problem and help policymakers to escape a "cheap talk" lobbying game. The welfare implications of these interactions depend on whether the policymakers' information or contracting problem predominates. Further, the policymaker's information problem may actually improve welfare outcomes. Similarly, financial contributions may also improve welfare outcomes. This dissertation includes unpublished co-authored material.

To learn the uncertainty of customer preference on the attribute of new product, usually a firm needs to do market research. Developing a product on an attribute which is less preferred by customer may lead to a failure. In addition, a firm used to take efforts to design the product. In recent years, we observed a new business model in which the firm does not take effort to design new product, nor does she do market research by herself. She provides rewards to attract outside designers to design new product. Some designers may take effort and design products based on their private information of customer preference. The firm receives designs with different quality and attribute, she chooses one to produce. By solving this game model, we get the equilibrium quality of the design offered by each designer based on their private cost parameter. And we obtain the following insights: When the market size is too small, the firm gives nothing to designers; when the market size is sufficiently big, the firm only gives reward to the designer whose design is produced; otherwise the firm gives both rewards to participated designers and the designer whose design is produced. We find that when the market size is big enough or the disutility is high enough, the new business model dominates the benchmark business model. When both the disutility and market size are small enough, the firm prefers the benchmark business model. And the relative attractiveness of new business model versus benchmark model keeps the same when the market size is small enough. The impact of extra reward on relative attractiveness of new business model versus benchmark model increases with extra reward. When the extra reward is high enough, the firm always prefers the new business model.

By purposefully utilising sensors, for instance by a datafusion system, the state of some system-relevant environmentmight be adequately assessed to support decision-making. Theever increasing access to sensors o.ers great opportunities,but alsoincurs grave challenges. As a result of managingmultiple sensors one can, e.g., expect to achieve a morecomprehensive, resolved, certain and more frequently updatedassessment of the environment than would be possible otherwise.Challenges include data association, treatment of con.ictinginformation and strategies for sensor coordination. We use the term information acquisition to denote the skillof a data fusion system to actively acquire information. Theaim of this thesis is to instructively situate that skill in ageneral context, explore and classify related research, andhighlight key issues and possible future work. It is our hopethat this thesis will facilitate communication, understandingand future e.orts for information acquisition. The previously mentioned trend towards utilisation of largesets of sensors makes us especially interested in large-scaleinformation acquisition, i.e., acquisition using many andpossibly spatially distributed and heterogeneous sensors. Information acquisition is a general concept that emerges inmany di.erent .elds of research. In this thesis, we surveyliterature from, e.g., agent theory, robotics and sensormanagement. We, furthermore, suggest a taxonomy of theliterature that highlights relevant aspects of informationacquisition. We describe a function, perception management (akin tosensor management), which realizes information acquisition inthe data fusion process and pertinent properties of itsexternal stimuli, sensing resources, and systemenvironment. An example of perception management is also presented. Thetask is that of managing a set of mobile sensors that jointlytrack some mobile targets. The game theoretic algorithmsuggested for distributing the targets among the sensors proveto be more robust to sensor failure than a measurement accuracyoptimal reference algorithm. <b>Keywords:</b>information acquisition, sensor management,resource management, information fusion, data fusion,perception management, game theory, target tracking / NR 20140805

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