2,527 research outputs found

    Towards a human eye behavior model by applying Data Mining Techniques on Gaze Information from IEC

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    In this paper, we firstly present what is Interactive Evolutionary Computation (IEC) and rapidly how we have combined this artificial intelligence technique with an eye-tracker for visual optimization. Next, in order to correctly parameterize our application, we present results from applying data mining techniques on gaze information coming from experiments conducted on about 80 human individuals

    Distributed Control of a Swarm of Autonomous Unmanned Aerial Vehicles

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    With the increasing use of Unmanned Aerial Vehicles (UAV)s military operations, there is a growing need to develop new methods of control and navigation for these vehicles. This investigation proposes the use of an adaptive swarming algorithm that utilizes local state information to influence the overall behavior of each individual agent in the swarm based upon the agent\u27s current position in the battlespace. In order to investigate the ability of this algorithm to control UAVs in a cooperative manner, a swarm architecture is developed that allows for on-line modification of basic rules. Adaptation is achieved by using a set of behavior coefficients that define the weight at which each of four basic rules is asserted in an individual based upon local state information. An Evolutionary Strategy (ES) is employed to create initial metrics of behavior coefficients. Using this technique, three distinct emergent swarm behaviors are evolved, and each behavior is investigated in terms of the ability of the adaptive swarming algorithm to achieve the desired emergent behavior by modifying the simple rules of each agent. Finally, each of the three behaviors is analyzed visually using a graphical representation of the simulation, and numerically, using a set of metrics developed for this investigation

    Exploration of Reaction Pathways and Chemical Transformation Networks

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    For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

    La Montología Global 4D: Hacia las Ciencias Convergentes y Transdisciplinarias de Montaña a través del Tiempo y el Espacio

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    With mountain studies we use integrative approaches for geoliteracy about productive socioecological landscapes, and motivate further transdisciplinary research in montology. We conceived this white paper as a confluence of individual expertise and collective reasoning towards forming synergistic research clusters dealing with convergent mountain science, to advance montology to a new level, whereby innovative thinking about sustainability science and regenerative development incorporates alternative propositions for maintenance, improvement, or regeneration of living conditions of mountainscapes. We seek to use this contemporary framing of sustainability and ecological restoration as the impetus to better understand nature-culture relations, framed on lived-in mountains that operate in four dimensions (length, width, depth, and time) oriented at maximizing the cross-cutting of themes around mountains as productive socioecological systems, in a new academic institutionalized convergent unit. We conclude with a call for consilient, sustainable, regenerative development in the world’s mountains.La utilización de los estudios de montaña requiere de narrativas integradoras para la geoalfabetización sobre paisajes socioecológicos productivos y motiva más investigaciones transdisciplinares en el campo de la montología. Concebimos este artículo como la confluencia de la experiencia individual y el razonamiento colectivo hacia la formación de grupos de investigación sinérgicos que se ocupan de la ciencia de montaña convergente, para hacer avanzar la montología a un nuevo nivel, mediante el cual el pensamiento innovador sobre la ciencia de la sustentabilidad y el desarrollo regenerativo incorpora propuestas alternativas para el mantenimiento, la mejora, o regeneración de las condiciones de vida de los paisajes de montaña. Buscamos utilizar este marco contemporáneo de sustentabilidad y restauración ecológica como el ímpetu para comprender mejor las relaciones de la naturaleza y la cultura, desde una perspectiva transdisciplinar, en montañas habitadas que operan en cuatro dimensiones (largo, ancho, alto y tiempo). El artículo está orientado a potenciar la transversalidad de temáticas en torno a las montañas como sistemas socioecológicos productivos, en una nueva disciplina académica institucionalizada y convergente. Concluimos con un llamado a un desarrollo regenerativo, sustentable y consiliente en las montañas del mundo

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

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    The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. In proposed research work, the user is aided by a visualization based on the representation of multidimensional Genetic Algorithm data on 2-0 space. The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. The user participates in the search by proposing a new individual. This is difTerent from existing Interactive Genetic Algorithm in which selection and evaluation of solutions is done by the users. A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. This visual tool enables the display of the evolution of gene values from generation to generation to observing and analysing the behaviour of the search space with user interactions. Individuals for the next generation are selected by using the objective function. Hence, a novel humanmachine interaction is developed in the proposed approach. The efficiency of the proposed approach is evaluated by two benchmark functions. The analysis and comparison of VIGA-20 is based on convergence test against the results obtained from the Simple Genetic Algorithm. This comparison is based on the same parameters except for the interactions of the user. The application of proposed approach is the modelling the branching structures by deriving a rule from best solution of VIGA-20. The comparison of results is based on the different user's perceptions, their involvement in the VIGA-20 and the difference of the fitness convergence as compared to Simple Genetic Algorithm

    Behavioral Strategy: Strategic Consensus, Power and Networks

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    Organizations are embedded in a network of relationships and make sense of their business environment through the cognitive frames of their employees and executives who constantly experience battles for power. This dissertation integrates strategic management research with organizational behavior to illuminate managerial cognition, intra-organizational power and interfirm networks. The collection of the studies presented in the present dissertation provides further insights into measurement of cognition, consensus formation process, optimal power differences, and social network theory with assumptions grounded on social cognition, behavioral decision theory, psychology and organizational behavior. These studies offered a new method to measure, visualize and aggregate individual cognition to group and between group level with a strong emphasis on multiple dimensions of cognition, shed light on micro-processes on consensus formation in relation to within-group power differences and psychological safety, a novel model of strategic decision making, and a new behavioral construct that refined existing theories from a behavioral perspective. Each study on its own laid down responses to core research questions of behavioral strategy. Consequently, this dissertation extends strategic management along behavioral lines and equips scholars and practitioners with novel methods and theoretical insights with respect to cognition, power and networks

    Workshop sensing a changing world : proceedings workshop November 19-21, 2008

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