2,259 research outputs found

    A Simple Theory of Every 'Thing'

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    One of the criteria to a strong principle in natural sciences is simplicity. This paper claims that the Free Energy Principle (FEP), by virtue of unifying particles with mind, is the simplest. Motivated by Hilbert’s 24th problem of simplicity, the argument is made that the FEP takes a seemingly mathematical complex domain and reduces it to something simple. More specifically, it is attempted to show that every ‘thing’, from particles to mind, can be partitioned into systemic states by virtue of self-organising symmetry break, i.e. self-entropy in terms of the balance between risk and ambiguity to achieve epistemic gain. By virtue of its explanatory reach, the FEP becomes the simplest principle under quantum, statistical and classical mechanics conditions

    A survey of self organisation in future cellular networks

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    This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

    Learning where to look with movement-based intrinsic motivations: a bio-inspired model

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    Most sophisticated mammals, in particular primates, interact with the world to acquire knowledge and skills later exploitable to obtain biologically relevant resources. These interactions are driven by intrinsic motivations. Recent research on brain is revealing the system of neural structures, pivoting on superior colliculus, underlying trial-and-error learning processes guided by movement-detection, one important element of one speci?c type of intrinsic motivation mechanism. Here we present a preliminary computational model of such system guiding the acquisition of overt attentional skills. The model is formed by bottom-up attentional components, exploiting the intrinsic properties of the scene, and top-down attentional components, learning under the guidance of movement-based intrinsic motivation. The model is tested with a simple task, inspired by the \u27gaze- contingency paradigm\u27 proposed in cognitive psychology, where looking some portions of the environment can directly change it. The tests of the model show how its integrated components can learn skills causing relevant changes in the environment while ignoring changes non-contingent to own action. The model also allows the presentation of a wider research agenda directed to build biologically plausible models of the interaction between overt attention control and intrinsic motivations

    Wind Disturbance Suppression in Autopilot Design

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    Environmental conditions affects ship’s course. Hence, it affects velocity, and efficiency of fuel consumption, which is an important research topic nowadays. Therefore, it is important to take it into account in the design of ship’s autopilots. In this paper a method is proposed to compensate for wind’s influence, which is based on wavelet transform by introducing the so called wavelet anti-filter. The anti-filter is added to the feed-forward branch of the classic autopilot design scheme, which consists of feedback loop and PID controller. The anti-filter branch represents a modification of the classic scheme
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