3 resultados para Segregation - Social and spatial
em DRUM (Digital Repository at the University of Maryland)
Resumo:
A fundamental problem in biology is understanding how and why things group together. Collective behavior is observed on all organismic levels - from cells and slime molds, to swarms of insects, flocks of birds, and schooling fish, and in mammals, including humans. The long-term goal of this research is to understand the functions and mechanisms underlying collective behavior in groups. This dissertation focuses on shoaling (aggregating) fish. Shoaling behaviors in fish confer foraging and anti-predator benefits through social cues from other individuals in the group. However, it is not fully understood what information individuals receive from one another or how this information is propagated throughout a group. It is also not fully understood how the environmental conditions and perturbations affect group behaviors. The specific research objective of this dissertation is to gain a better understanding of how certain social and environmental factors affect group behaviors in fish. I focus on two ecologically relevant decision-making behaviors: (i) rheotaxis, or orientation with respect to a flow, and (ii) startle response, a rapid response to a perceived threat. By integrating behavioral and engineering paradigms, I detail specifics of behavior in giant danio Devario aequipinnatus (McClelland 1893), and numerically analyze mathematical models that may be extended to group behavior for fish in general, and potentially other groups of animals as well. These models that predict behavior data, as well as generate additional, testable hypotheses. One of the primary goals of neuroethology is to study an organism's behavior in the context of evolution and ecology. Here, I focus on studying ecologically relevant behaviors in giant danio in order to better understand collective behavior in fish. The experiments in this dissertation provide contributions to fish ecology, collective behavior, and biologically-inspired robotics.
Resumo:
The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.
Resumo:
This research examines the process of placemaking in LeDroit Park, a residential Washington, DC, neighborhood with a historic district at its core. Unpacking the entwined physical and social evolution of the small community within the context of the Nation’s Capital, this analysis provides insight into the role of urban design and development as well as historic designation on shaping collective identity. Initially planned and designed in 1873 as a gated suburb just beyond the formal L’Enfant-designed city boundary, LeDroit Park was intended as a retreat for middle and upper-class European Americans from the growing density and social diversity of the city. With a mixture of large romantic revival mansions and smaller frame cottages set on grassy plots evocative of an idealized rural village, the physical design was intentionally inwardly-focused. This feeling of refuge was underscored with a physical fence that surrounded the development, intended to prevent African Americans from nearby Howard University and the surrounding neighborhood, from using the community’s private streets to access the City of Washington. Within two decades of its founding, LeDroit Park was incorporated into the District of Columbia, the surrounding fence was demolished, and the neighborhood was racially integrated. Due to increasingly stringent segregation laws and customs in the city, this period of integration lasted less than twenty years, and LeDroit Park developed into an elite African American enclave, using the urban design as a bulwark against the indignities of a segregated city. Throughout the 20th century housing infill and construction increased density, yet the neighborhood never lost the feeling of security derived from the neighborhood plan. Highlighting the architecture and street design, neighbors successfully received historic district designation in 1974 in order to halt campus expansion. After a stalemate that lasted two decades, the neighborhood began another period of transformation, both racial and socio-economic, catalyzed by a multi-pronged investment program led by Howard University. Through interviews with long-term and new community members, this investigation asserts that the 140-year development history, including recent physical interventions, is integral to placemaking, shaping the material character as well as the social identity of residents.