18 research outputs found

    Backdoors to planning

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    Backdoors measure the distance to tractable fragments and have become an important tool to find fixed-parameter tractable (fpt) algorithms for hard problems in AI and beyond. Despite their success, backdoors have not been used for planning, a central problem in AI that has a high computational complexity. In this work, we introduce two notions of backdoors building upon the causal graph. We analyze the complexity of finding a small backdoor (detection) and using the backdoor to solve the problem (evaluation) in the light of planning with (un)bounded plan length/domain of the variables. For each setting we present either an fpt-result or rule out the existence thereof by showing parameterized intractability. For several interesting cases we achieve the most desirable outcome: detection and evaluation are fpt. In addition, we explore the power of polynomial preprocessing for all fpt-results, i.e., we investigate whether polynomial kernels exist. We show that for the detection problems, polynomial kernels exist whereas we rule out the existence of polynomial kernels for the evaluation problems

    Identification of research communities in cited and uncited publications using a co-authorship network

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    Patterns of co-authorship provide an effective means of probing the structures of research communities. In this paper, we use the CiteSpace social network tool and co-authorship data from the Web of Science to analyse two such types of community. The first type is based on the cited publications of a group of highly productive authors in a particular discipline, and the second on the uncited publications of those highly productive authors. These pairs of communities were generated for three different countries—the People’s Republic of China (PRC), the United Kingdom (UK) and the United States of America (USA)—and for four different disciplines (as denoted by Web of Science subject categories)—Chemistry Organic, Engineering Environmental, Economics, and Management. In the case of the UK and USA, the structures of the cited and uncited communities in each of the four disciplines were markedly different from each other; in the case of the PRC, conversely, the cited and uncited PRC communities had broadly similar structures that were characterised by large groups of connected authors. We suggest that this may arise from a greater degree of guest or honorary authorship in the PRC than in the UK or the USA

    A Pre-specified Blockmodeling to Analyze Structural Dynamics in Innovation Networks

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    In recent decades economic theory has highlighted the benefits produced by networks of organizations in fostering innovation. A number of public policies were put in place to favor these innovation networks throughout Europe. The top-down institution of a number of specialized technological districts in Italy has been one of the main outcomes of this new wave of policies, in mid-2000. The aim of this paper is to explore what impact the institution of technological districts had on collaborative patterns over time. Using a pre-specified blockmodeling, observed network configurations obtained by the co-participation to R&D projects undertaken by organizations involved in a technological district are compared with a theoretical core-periphery structure in a 8-years time interval. The analyses of networks over time show that collaborative patterns have evolved from a core-periphery structure towards a complete network in which each research group is connected with the others
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