1,164 research outputs found

    The challenge of complexity for cognitive systems

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    Complex cognition addresses research on (a) high-level cognitive processes – mainly problem solving, reasoning, and decision making – and their interaction with more basic processes such as perception, learning, motivation and emotion and (b) cognitive processes which take place in a complex, typically dynamic, environment. Our focus is on AI systems and cognitive models dealing with complexity and on psychological findings which can inspire or challenge cognitive systems research. In this overview we first motivate why we have to go beyond models for rather simple cognitive processes and reductionist experiments. Afterwards, we give a characterization of complexity from our perspective. We introduce the triad of cognitive science methods – analytical, empirical, and engineering methods – which in our opinion have all to be utilized to tackle complex cognition. Afterwards we highlight three aspects of complex cognition – complex problem solving, dynamic decision making, and learning of concepts, skills and strategies. We conclude with some reflections about and challenges for future research

    Areas of Attention for Image Captioning

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    We propose "Areas of Attention", a novel attention-based model for automatic image captioning. Our approach models the dependencies between image regions, caption words, and the state of an RNN language model, using three pairwise interactions. In contrast to previous attention-based approaches that associate image regions only to the RNN state, our method allows a direct association between caption words and image regions. During training these associations are inferred from image-level captions, akin to weakly-supervised object detector training. These associations help to improve captioning by localizing the corresponding regions during testing. We also propose and compare different ways of generating attention areas: CNN activation grids, object proposals, and spatial transformers nets applied in a convolutional fashion. Spatial transformers give the best results. They allow for image specific attention areas, and can be trained jointly with the rest of the network. Our attention mechanism and spatial transformer attention areas together yield state-of-the-art results on the MSCOCO dataset.o meaningful latent semantic structure in the generated captions.Comment: Accepted in ICCV 201

    Vision Research Agenda to 2025

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    The TP Organics Vision Research Agenda was prepared between June 2007 and July 2008 on the basis of wide-ranging discussions with farmers’ organizations, scientists, organic traders and retailers, and EU-wide umbrella organizations representing a variety of commercial, non-commercial and civil interests. Up to now, research projects and national framework programmes on organic agriculture have addressed immediate technology gaps in organic agriculture and food production. This Vision has been politically expedient and has given rise to a greater number of producers and professional skills for the task of serving unexpectedly fast growing consumer driven markets. Thus, many organic research projects had a short term perspective only. In contrast to this, our vision takes a long-term perspective on the research needs of organic agriculture and food systems. The three strategic research priorities presented in the vision focus in particular on the inconsistencies between economy, ecology and social cohesion in agriculture and food production and propose research activities and insightful learning concepts for organic and other farming systems

    The labor market effects of housing subsidies: evidence from Switzerland

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    There is an active debate about whether housing assistance policies distort labor market incentives. We investigate the so far neglected interaction between housing subsidy recipients’ residential mobility and their job mobility. The setting for this is a large-scale, object-targeting housing assistance program in Switzerland launched in 1975. The WEG program offered substantial rent subsidies to low-income households for a limited duration. Leveraging variation in the timing of subsidy expiration in an event study, we show that WEG tenants have reduced residential mobility as long as subsidies are paid out but increase mobility once subsidies expire. Recipients’ labor market response to subsidy expiration, however, is limited or even negative. Furthermore, we find that WEG out-movers, on average, experience an improvement in dwelling and neighborhood quality, but there is large variation in outcomes

    How to Measure the Game Experience? Analysis of the Factor Structure of Two Questionnaires

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    We describe and report the analysis of two widely used questionnaires to measure the player experience in digital games. In order to contribute to the further validation and meaningful application of the PENS and GEQ we examined the underlying factorial structure of both questionnaires. Four hundred and forty-seven participants played two different games and rated them on a set of various variables including the PENS and GEQ. Consistent with previous research we gained additional insight into optimization of both measurements. While the factor structure of the PENS appears to be consistent and invariant across two different games, the GEQ reveals weaknesses in fulfilling these requirements

    Consistent SDNs through Network State Fuzzing

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    The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Unfortunately, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part. Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to periodically test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly while outperforming baseline approaches.Comment: Added three extra relevant references, the arXiv later was accepted in IEEE Transactions of Network and Service Management (TNSM), 2019 with the title "Towards Consistent SDNs: A Case for Network State Fuzzing

    Methodical procedure for a surrogate model based fatigue calculation to support the design process of eBike drive units

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    In this paper, a method is developed to consider multiaxial load spectra and their variation in a computationally efficient local fatigue calculation procedure. This method is based on an FE data-based surrogate model and is intended to support the simulation-based product design process. To demonstrate their application and necessity, a case study on the design of eBike drive units is presented. For this purpose, the general requirements for the design of eBike drive units as well as the fundamentals of multiaxial fatigue analysis and surrogate modeling are outlined. In addition, a validation process of the surrogate model and its use for fatigue calculation is presented and discussed

    Online Playtesting With Crowdsourcing: Advantages and Challenges

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    Answering important design questions and delivering actionable insights within a couple of days is invaluable. Traditional playtests are often time consuming, expensive and deliver insights based on only a small sample of participants. Crowdsourced playtests may deliver comparable quality of feedback with less resources. However, several aspects have to be considered in order to receive meaningful and actionable results. Based on our experience, we provide five recommendations to ensure data quality and prevent fraud. Taken together, this suggests that crowd-sourced playtesting is a promising alternative for indie, non-profit and academic Games User Research

    Panopticon: Reaping the Benefits of Partial SDN Deployment in Enterprise Networks

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    The operational challenges posed in enterprise networks, present an appealing opportunity for the software-defined orchestration of the network (SDN). However, the primary challenge to realizing solutions built on SDN in the enterprise is the deployment problem. Unlike in the data-center, network upgrades in the enterprise start with the existing deployment and are budget and resource-constrained. In this work, we investigate the prospect for partial Software Defined Network (SDN) deployment. We present Panopticon, an architecture and methodology for planning and operating networks that combine legacy and upgraded SDN switches. Panopticon exposes an abstraction of a logical SDN in a partially upgraded legacy network, where the SDN benefits extend potentially over the entire network. We evaluate the feasibility of our approach through simulation on real enterprise campus network topologies entailing over 1500 switches and routers. Our results suggest that with only a handful of upgraded switches, it becomes possible to operate most of an enterprise network as a single SDN while meeting key resource constraints
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