915 research outputs found

    Herding an Adversarial Attacker to a Safe Area for Defending Safety-Critical Infrastructure

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    This paper investigates a problem of defending safety-critical infrastructure from an adversarial aerial attacker in an urban environment. A circular arc formation of defenders is formed around the attacker, and vector-field based guidance laws herd the attacker to a predefined safe area in the presence of rectangular obstacles. The defenders' formation is defined based on a novel vector field that imposes super-elliptic contours around the obstacles, to closely resemble their rectangular shape. A novel finite-time stabilizing controller is proposed to guide the defenders to their desired formation while avoiding obstacles and inter-agent collisions. The efficiency of the approach is demonstrated via simulation results.Comment: ACC 201

    Social Learning in Continuous Time - When are Informational Cascades More Likely to be Inefficient?

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    In an observational learning environment rational agents may mimic the actions of the predecessors even when their own signal suggests the opposite. In case early movers’ signals happen to be incorrect society may settle on a common inefficient action, resulting in an inefficient informational cascade. This paper models observational learning in continuous time with endogenous timing of moves. This permits the analysis of comparative statics results. The effect of an increase in signal quality on the likelihood of an inefficient cascade is shown to be nonmonotonic. If agents do not have strong priors, an increase in signal quality may lead to a higher probability of inefficient herding. The analysis also suggests that markets with quick response to investment decisions, such as financial markets, may be more prone to inefficient collapses.Comparative Statics, Herding, Herd Manipulation

    From systems to patterns and back - Exploring the spatial role of dynamic time and direction patterns in the area of regional planning

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    This master thesis presents a data-driven framework to explore the role of dynamic time and direction patterns in the area of Finnish Lapland in order to improve decision-making in urban planning and design tasks. The Arctic Ocean Railway project is chosen as a case study. In an era marked by dramatic environmental, political and societal changes, the Arctic region becomes more global and complex. An increasing number of actors are involved in its spatial transformations. Due to melting ice, the Northern Sea Route gains attention from the shipping and trade industries that are manifested in new port and infrastructure projects. Eco-tourism is booming in the Arctic due to its imaginary remoteness, while local Indigenous People try to preserve traditional livelihoods. In order to cope with the increasing complexity of such dynamic urban and regional challenges, Systems Thinking, dynamic patterns, modelling and use of simulation are researched to open up novel ways for complex regional planning methods. This is achieved by designing an agent-based model and using different representation and abstraction features for different dynamic data packages. The project is integrated within the GAMA simulation platform (a modelling and simulation development environment for building spatially explicit agent-based simulations) and embedded in the MIT CityScope framework - a medium for both, analyzing agent’s behavioural patterns and displaying them to the relevant stakeholders. The project attempts to address the necessity to handle the increasing complexity by presenting a dynamic, evidence-based planning and decision support tool called CityScope Lapland. The main goal of CityScope Lapland is to use digital technologies to incorporate variables like time and direction in urban spatial analysis and methodology; secondly, to improve the accessibility of the decision-making process for non-experts through a tangible user interface, and third, to help users evaluate their decisions by creating a feedback through real-time visualization of urban simulation results when facing less and less predictable futures. The project provides an alternative design approach, introducing new forms of urban imagination and different ways of perceiving and measuring complex spatial transformations

    An Equilibrium Model of User Generated Content

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    This paper considers the joint creation and consumption of content on user generated content platforms (e.g., reviews or articles, chat, videos, etc.). On these platforms, users’ utilities depend upon the participation of others; hence, users’ expectations regarding the participation of others on the site becomes germane to their own involvement levels. Yet these beliefs are often assumed to be fixed. Accordingly, we develop a dynamic rational expectations equilibrium model of joint consumption and generation of information. We estimate the model on a novel data set from a large Internet forum site and use the model to offer recommendations regarding site strategy. Results indicate that beliefs play a major role in UGC, ignoring these beliefs leads to erroneous inferences about consumer behavior, and that these beliefs have an important implications for the marketing strategy of UGC sites. We find that user and site generated content can be either strategic complements or substitutes depending on whether the competition for existing readers exceeds the potential to attract new ones. In our data, the competitive effect substantially dilutes the market expansion effect of site generated content. Likewise, past and current content can also be either strategic substitutes or complements. Results indicate more durable content increases overall site participation, suggesting that the site should invest in making past information easier to find (via better search or page design). Third, because content consumption and generation interact, it is unclear which factor dominates in network growth. We find that decreasing content consumption costs (perhaps by changing site design or via search tools) enhances site engagement more than decreasing content generating costs. Overall, enhancing content durability and reducing content consumption cost appear to be the most effective strategies for increasing site visitation

    Part 3: Systemic risk in ecology and engineering

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    The Federal Reserve Bank of New York released a report -- New Directions for Understanding Systemic Risk -- that presents key findings from a cross-disciplinary conference that it cosponsored in May 2006 with the National Academy of Sciences' Board on Mathematical Sciences and Their Applications. ; The pace of financial innovation over the past decade has increased the complexity and interconnectedness of the financial system. This development is important to central banks, such as the Federal Reserve, because of their traditional role in addressing systemic risks to the financial system. ; To encourage innovative thinking about systemic issues, the New York Fed partnered with the National Academy of Sciences to bring together more than 100 experts on systemic risk from 22 countries to compare cross-disciplinary perspectives on monitoring, addressing and preventing this type of risk. ; This report, released as part of the Bank's Economic Policy Review series, outlines some of the key points concerning systemic risk made by the various disciplines represented - including economic research, ecology, physics and engineering - as well as presentations on market-oriented models of financial crises, and systemic risk in the payments system and the interbank funds market. The report concludes with observations gathered from the sessions and a discussion of potential applications to policy. ; The three papers presented in this conference session highlighted the positive feedback effects that produce herdlike behavior in markets, and the subsequent discussion focused in part on means of encouraging heterogeneous investment strategies to counter such behavior. Participants in the session also discussed the types of models used to study systemic risk and commented on the challenges and trade-offs researchers face in developing their models.Financial risk management ; Financial markets ; Financial stability ; Financial crises
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