1,420 research outputs found

    Building Machines That Learn and Think Like People

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    Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and board games, achieving performance that equals or even beats humans in some respects. Despite their biological inspiration and performance achievements, these systems differ from human intelligence in crucial ways. We review progress in cognitive science suggesting that truly human-like learning and thinking machines will have to reach beyond current engineering trends in both what they learn, and how they learn it. Specifically, we argue that these machines should (a) build causal models of the world that support explanation and understanding, rather than merely solving pattern recognition problems; (b) ground learning in intuitive theories of physics and psychology, to support and enrich the knowledge that is learned; and (c) harness compositionality and learning-to-learn to rapidly acquire and generalize knowledge to new tasks and situations. We suggest concrete challenges and promising routes towards these goals that can combine the strengths of recent neural network advances with more structured cognitive models.Comment: In press at Behavioral and Brain Sciences. Open call for commentary proposals (until Nov. 22, 2016). https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/information/calls-for-commentary/open-calls-for-commentar

    Modelling Cell Cycle using Different Levels of Representation

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    Understanding the behaviour of biological systems requires a complex setting of in vitro and in vivo experiments, which attracts high costs in terms of time and resources. The use of mathematical models allows researchers to perform computerised simulations of biological systems, which are called in silico experiments, to attain important insights and predictions about the system behaviour with a considerably lower cost. Computer visualisation is an important part of this approach, since it provides a realistic representation of the system behaviour. We define a formal methodology to model biological systems using different levels of representation: a purely formal representation, which we call molecular level, models the biochemical dynamics of the system; visualisation-oriented representations, which we call visual levels, provide views of the biological system at a higher level of organisation and are equipped with the necessary spatial information to generate the appropriate visualisation. We choose Spatial CLS, a formal language belonging to the class of Calculi of Looping Sequences, as the formalism for modelling all representation levels. We illustrate our approach using the budding yeast cell cycle as a case study

    The RSZ BASIC programming language manual

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    The RSZ BASIC interactive language is described. The RSZ BASIC interpreter is resident in the Telemetry Data Processor, a system dedicated to the processing and displaying of PCM telemetry data. A series of working examples teaches the fundamentals of RSZ BASIC and shows how to construct, edit, and manage storage of programs

    The BATSE Gamma-Ray Burst Spectral Catalog. I. High Time Resolution Spectroscopy of Bright Bursts using High Energy Resolution Data

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    This is the first in a series of gamma-ray burst spectroscopy catalogs from the Burst And Transient Source Experiment (BATSE) on the Compton Gamma Ray Observatory, each covering a different aspect of burst phenomenology. In this paper, we present time-sequences of spectral fit parameters for 156 bursts selected for either their high peak flux or fluence. All bursts have at least eight spectra in excess of 45 sigma above background and span burst durations from 1.66 to 278 s. Individual spectral accumulations are typically 128 ms long at the peak of the brightest events, but can be as short as 16 ms, depending on the type of data selected. We have used mostly high energy resolution data from the Large Area Detectors, covering an energy range of typically 28 - 1800 keV. The spectral model chosen is from a small empirically-determined set of functions, such as the well-known `GRB' function, that best fits the time-averaged burst spectra. Thus, there are generally three spectral shape parameters available for each of the 5500 total spectra: a low-energy power-law index, a characteristic break energy and possibly a high-energy power-law index. We present the distributions of the observed sets of these parameters and comment on their implications. The complete set of data that accompanies this paper is necessarily large, and thus is archived electronically at: http://www.journals.uchicago.edu/ApJ/journal/.Comment: Accepted for publication: ApJS, 125. 38 pages, 9 figures; supplementary electronic archive to be published by ApJ; available from lead author upon reques

    Constructing runtime models with bigraphs to address ubiquitous computing service composition volatility

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    In this thesis, we explore the appropriateness of the language abstractions provided by Bigraphs to construct a model at runtime to tackle the problem of volatility in a service composition running on a mobile device. Our contributions to knowledge are as follows: 1) We have shown that Bigraphs (Milner, 2009) are suitable for expressing models at runtime. 2) We have offered Bigraph language abstractions as an appropriate solution to some of the research problems posed by the models at runtime community (Aßmann et al., 2012). 3) We have discussed the general lessons learnt from using Bigraphs for a practical application such as a model at runtime. 4) We have discussed the general lessons learnt from our experiences of designing models at runtime. 5) We have implemented the model at runtime using the BPL Tool (ITU, 2011) and have experimentally studied the response times of our Bigraphical model. We have suggested appropriate enhancements for the tool based on our experiences. We present techniques to parameterize the reaction rules so that the matching algorithm of the BPL Tool returns a single match giving us the ability to dynamically program the model at runtime. We also show how to query the Bigraph structure
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