22,835 research outputs found

    Agent-Based Computational Economics

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    Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Starting from initial conditions, specified by the modeler, the computational economy evolves over time as its constituent agents repeatedly interact with each other and learn from these interactions. ACE is therefore a bottom-up culture-dish approach to the study of economic systems. This study discusses the key characteristics and goals of the ACE methodology. Eight currently active research areas are highlighted for concrete illustration. Potential advantages and disadvantages of the ACE methodology are considered, along with open questions and possible directions for future research.Agent-based computational economics; Autonomous agents; Interaction networks; Learning; Evolution; Mechanism design; Computational economics; Object-oriented programming.

    The role of urban built heritage in qualify and quantify resilience. Specific issues in Mediterranean city

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    The Mediterranean city represents a significant example of urban organism, based on masonry construction and characterized by typological processes of growth. The material consistency and the temporal continuity of built heritage in Mediterranean city make relevant its interpretation and analysis according to the resilient approach. The declination of this approach in many disciplines generated a substantial diversity among the definitions of resilience (Francis and Bekera, 2014). Consequently, frameworks, adopted for a quantitative or qualitative assessment, underline the lack of standardization and rigor in defining resilience measurements. A review of resilience literature and actual applications in urban context permit to understand that there are different operators working on the field: on the one hand there are international organizations, on the other hand there are academics. The review of both the two ambits of investigation intends to clarify specific properties and convergence points in order to trace an evolution of conceptual framework and to identify general features of urban resilience. This process is fundamental in focusing the main aims of the research program: the definition of the role of urban built heritage, given by the close correlation between masonry constructive technique, typologies and morphologies, its material value in urban system, and its relevance in Mediterranean city in constitution of urban resilience (UNISDR, 2012a). Despite an increasing number of academic studies concerning the role of built environment in defining and improving cities resilience, their major attention is still focused on street patterns and lifelines infrastructures. The paper concludes how the role of built heritage remains insufficiently explored and a correct definition of urban structure is still missing inside the domain of infrastructural resilience

    On the Role of Social Identity and Cohesion in Characterizing Online Social Communities

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    Two prevailing theories for explaining social group or community structure are cohesion and identity. The social cohesion approach posits that social groups arise out of an aggregation of individuals that have mutual interpersonal attraction as they share common characteristics. These characteristics can range from common interests to kinship ties and from social values to ethnic backgrounds. In contrast, the social identity approach posits that an individual is likely to join a group based on an intrinsic self-evaluation at a cognitive or perceptual level. In other words group members typically share an awareness of a common category membership. In this work we seek to understand the role of these two contrasting theories in explaining the behavior and stability of social communities in Twitter. A specific focal point of our work is to understand the role of these theories in disparate contexts ranging from disaster response to socio-political activism. We extract social identity and social cohesion features-of-interest for large scale datasets of five real-world events and examine the effectiveness of such features in capturing behavioral characteristics and the stability of groups. We also propose a novel measure of social group sustainability based on the divergence in group discussion. Our main findings are: 1) Sharing of social identities (especially physical location) among group members has a positive impact on group sustainability, 2) Structural cohesion (represented by high group density and low average shortest path length) is a strong indicator of group sustainability, and 3) Event characteristics play a role in shaping group sustainability, as social groups in transient events behave differently from groups in events that last longer

    The International Monetary System: An Assessment and Avenue for Reform

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    The current international monetary system is in need of reform. This article first provides an assessment of the existing system, highlighting both its strengths and weaknesses. It notes that the system has not facilitated the symmetric and timely adjustment in the real exchange rate necessary to accommodate the integration of China and other emerging-market economies into the global economy. This lack of adjustment contributed to the global financial crisis and recession and, because it is forestalling the required rotation of global demand, is hindering the global recovery. The article then discusses reform of the system that would see all systemically important countries and currency areas adopt market-based and convertible floating exchange rates supported by appropriate monetary, fiscal and financial sector policy frameworks. It also examines the roles of the G-20 countries and major international financial institutions in promoting and facilitating the system’s transition.

    Vulnerability analysis of satellite-based synchronized smart grids monitoring systems

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    The large-scale deployment of wide-area monitoring systems could play a strategic role in supporting the evolution of traditional power systems toward smarter and self-healing grids. The correct operation of these synchronized monitoring systems requires a common and accurate timing reference usually provided by a satellite-based global positioning system. Although these satellites signals provide timing accuracy that easily exceeds the needs of the power industry, they are extremely vulnerable to radio frequency interference. Consequently, a comprehensive analysis aimed at identifying their potential vulnerabilities is of paramount importance for correct and safe wide-area monitoring system operation. Armed with such a vision, this article presents and discusses the results of an experimental analysis aimed at characterizing the vulnerability of global positioning system based wide-area monitoring systems to external interferences. The article outlines the potential strategies that could be adopted to protect global positioning system receivers from external cyber-attacks and proposes decentralized defense strategies based on self-organizing sensor networks aimed at assuring correct time synchronization in the presence of external attacks

    Phase Space Localization and Approach to Thermal Equilibrium for a Class of Open Systems

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    We analyse the evolution of a quantum oscillator in a finite temperature environment using the quantum state diffusion (QSD) picture. Following a treatment similar to that of reference [7] we identify stationary solutions of the corresponding It\^o equation. We prove their global stability and compute typical time scales characterizing the localization process. The recovery of the density matrix in approximately diagonal form enables us to verify the approach to thermal equilibrium in the long time limit and we comment on the connection between QSD and the decoherent histories approach.Comment: 10 pages, Late

    Topological and Dynamical Complexity of Random Neural Networks

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    Random neural networks are dynamical descriptions of randomly interconnected neural units. These show a phase transition to chaos as a disorder parameter is increased. The microscopic mechanisms underlying this phase transition are unknown, and similarly to spin-glasses, shall be fundamentally related to the behavior of the system. In this Letter we investigate the explosion of complexity arising near that phase transition. We show that the mean number of equilibria undergoes a sharp transition from one equilibrium to a very large number scaling exponentially with the dimension on the system. Near criticality, we compute the exponential rate of divergence, called topological complexity. Strikingly, we show that it behaves exactly as the maximal Lyapunov exponent, a classical measure of dynamical complexity. This relationship unravels a microscopic mechanism leading to chaos which we further demonstrate on a simpler class of disordered systems, suggesting a deep and underexplored link between topological and dynamical complexity

    Experimental effects and causal representations

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    In experimental settings, scientists often “make” new things, in which case the aim is to intervene in order to produce experimental objects and processes—characterized as ‘effects’. In this discussion, I illuminate an important performative function in measurement and experimentation in general: intervention-based experimental production (IEP). I argue that even though the goal of IEP is the production of new effects, it can be informative for causal details in scientific representations. Specifically, IEP can be informative about causal relations in: regularities under study; ‘intervention systems’, which are measurement/experimental systems; and new technological systems
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