74,939 research outputs found

    A multi-agent based evolutionary algorithm in non-stationary environments

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    This article is posted here with permission of IEEE - Copyright @ 2008 IEEEIn this paper, a multi-agent based evolutionary algorithm (MAEA) is introduced to solve dynamic optimization problems. The agents simulate living organism features and co-evolve to find optimum. All agents live in a lattice like environment, where each agent is fixed on a lattice point. In order to increase the energy, agents can compete with their neighbors and can also acquire knowledge based on statistic information. In order to maintain the diversity of the population, the random immigrants and adaptive primal dual mapping schemes are used. Simulation experiments on a set of dynamic benchmark problems show that MAEA can obtain a better performance in non-stationary environments in comparison with several peer genetic algorithms.This work was suported by the Key Program of National Natural Science Foundation of China under Grant No. 70431003, the Science Fund for Creative Research Group of the National Natural Science Foundation of China under Grant No. 60521003, the National Science and Technology Support Plan of China under Grant No. 2006BAH02A09, and the Engineering and Physical Sciences Research Council of the United Kingdom under Grant No. EP/E060722/1

    Re-visions of rationality?

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    Empirical evidence suggests proponents of the ‘adaptive toolbox’ framework of human judgment need to rethink their vision of rationality

    Herbert Simon's decision-making approach: Investigation of cognitive processes in experts

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    This is a post print version of the article. The official published can be obtained from the links below - PsycINFO Database Record (c) 2010 APA, all rights reserved.Herbert Simon's research endeavor aimed to understand the processes that participate in human decision making. However, despite his effort to investigate this question, his work did not have the impact in the “decision making” community that it had in other fields. His rejection of the assumption of perfect rationality, made in mainstream economics, led him to develop the concept of bounded rationality. Simon's approach also emphasized the limitations of the cognitive system, the change of processes due to expertise, and the direct empirical study of cognitive processes involved in decision making. In this article, we argue that his subsequent research program in problem solving and expertise offered critical tools for studying decision-making processes that took into account his original notion of bounded rationality. Unfortunately, these tools were ignored by the main research paradigms in decision making, such as Tversky and Kahneman's biased rationality approach (also known as the heuristics and biases approach) and the ecological approach advanced by Gigerenzer and others. We make a proposal of how to integrate Simon's approach with the main current approaches to decision making. We argue that this would lead to better models of decision making that are more generalizable, have higher ecological validity, include specification of cognitive processes, and provide a better understanding of the interaction between the characteristics of the cognitive system and the contingencies of the environment

    UTHM water quality classification based on sub index

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    River or stream at their source is unpolluted, but as water flow downstream, the river or lake is receiving point and non-point pollutant source. Ammoniacal nitrogen (NH3- N) and suspended solids (SS) strongly influences the dynamics of the dissolved oxygen in the water. Studies on monitoring this parameter were conducted for a river or lake but limited to the small man-made lake. This study is initiate to determine the changes in water quality of UTHM watershed as the water flows from upstream to downstream. The monitoring of NH3-N and TSS were monitored at two sampling schemes, 1) at the two-week interval and, 2) at a daily basis followed by the determination of the water quality sub-index particularly SIAN and SISS. The results showed that the two lakes in UTHM watershed were classified as polluted. In conclusion, the remedial action should be implemented to improve the water quality to meet the requirements at least to meet the recreational purpose

    SPHERE: the exoplanet imager for the Very Large Telescope

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    Observations of circumstellar environments to look for the direct signal of exoplanets and the scattered light from disks has significant instrumental implications. In the past 15 years, major developments in adaptive optics, coronagraphy, optical manufacturing, wavefront sensing and data processing, together with a consistent global system analysis have enabled a new generation of high-contrast imagers and spectrographs on large ground-based telescopes with much better performance. One of the most productive is the Spectro-Polarimetic High contrast imager for Exoplanets REsearch (SPHERE) designed and built for the ESO Very Large Telescope (VLT) in Chile. SPHERE includes an extreme adaptive optics system, a highly stable common path interface, several types of coronagraphs and three science instruments. Two of them, the Integral Field Spectrograph (IFS) and the Infra-Red Dual-band Imager and Spectrograph (IRDIS), are designed to efficiently cover the near-infrared (NIR) range in a single observation for efficient young planet search. The third one, ZIMPOL, is designed for visible (VIR) polarimetric observation to look for the reflected light of exoplanets and the light scattered by debris disks. This suite of three science instruments enables to study circumstellar environments at unprecedented angular resolution both in the visible and the near-infrared. In this work, we present the complete instrument and its on-sky performance after 4 years of operations at the VLT.Comment: Final version accepted for publication in A&

    Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation

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    Many modern computer vision and machine learning applications rely on solving difficult optimization problems that involve non-differentiable objective functions and constraints. The alternating direction method of multipliers (ADMM) is a widely used approach to solve such problems. Relaxed ADMM is a generalization of ADMM that often achieves better performance, but its efficiency depends strongly on algorithm parameters that must be chosen by an expert user. We propose an adaptive method that automatically tunes the key algorithm parameters to achieve optimal performance without user oversight. Inspired by recent work on adaptivity, the proposed adaptive relaxed ADMM (ARADMM) is derived by assuming a Barzilai-Borwein style linear gradient. A detailed convergence analysis of ARADMM is provided, and numerical results on several applications demonstrate fast practical convergence.Comment: CVPR 201

    To act fast or to bide time? Adaptive exploration under competitive pressure

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