8,773 research outputs found

    Fitness and novelty in evolutionary art

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    In this paper the effects of introducing novelty search in evolutionary art are explored. Our algorithm combines fitness and novelty metrics to frame image evolution as a multi-objective optimisation problem, promoting the creation of images that are both suitable and diverse. The method is illustrated by using two evolutionary art engines for the evolution of figurative objects and context free design grammars. The results demonstrate the ability of the algorithm to obtain a larger set of fit images compared to traditional fitness-based evolution, regardless of the engine used

    A comparative study of the molecular evolution of signalling pathway members across olfactory, gustatory and photosensory modalities

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    All sensory modalities serve a similar objective, which is to decode input by making predictions in time and space about an animal’s surroundings. The evolution of sensory modalities is driven by the need to shape effective behavioural outputs, and in turn increase survival. Throughout evolution, sensory systems have undergone a great deal of specialization; and even though some modalities are derived from unique origins within different phyla, they still exhibit many common design features (Strausfeld and Hildebrand 1999; Eisthen 2002; Jacobs et al. 2007). We now have detailed mechanistic data on how sensory systems operate within specific animals (Buck and Axel 1991; Chalasani et al. 2007; Sato et al. 2008; Wicher et al. 2008), however it is still not clear how sensory signalling pathways evolve at the molecular level, and whether these evolutionary mechanisms are shared between diverse taxa. Here we set out to investigate the molecular evolution of signalling pathway members across olfactory, gustatory, and photosensory modalities from very divergent phyla in an attempt to develop a model of molecular evolution for sensory systems. From our pairwise intraphylum analysis we found that sensory signalling pathways unusually undergo high levels of functional constraint that are higher than genomewide global levels of constraint, and this purifying selection is common within the very divergent taxa we examined. We also find that gene duplication events represent a conserved but heterogeneous driver of evolution within sensory signalling pathways. Taken together, we propose a ‘sessile’ mechanism of sensory signalling pathway evolution, which on one side facilitates bursts of gene duplication and relaxed selection and on the other side it is unusually anchored by high levels of selective constraint that preserves core sensory function

    A comparative study of the molecular evolution of signalling pathway members across olfactory, gustatory and photosensory modalities

    Get PDF
    All sensory modalities serve a similar objective, which is to decode input by making predictions in time and space about an animal’s surroundings. The evolution of sensory modalities is driven by the need to shape effective behavioural outputs, and in turn increase survival. Throughout evolution, sensory systems have undergone a great deal of specialization; and even though some modalities are derived from unique origins within different phyla, they still exhibit many common design features (Strausfeld and Hildebrand 1999; Eisthen 2002; Jacobs et al. 2007). We now have detailed mechanistic data on how sensory systems operate within specific animals (Buck and Axel 1991; Chalasani et al. 2007; Sato et al. 2008; Wicher et al. 2008), however it is still not clear how sensory signalling pathways evolve at the molecular level, and whether these evolutionary mechanisms are shared between diverse taxa. Here we set out to investigate the molecular evolution of signalling pathway members across olfactory, gustatory, and photosensory modalities from very divergent phyla in an attempt to develop a model of molecular evolution for sensory systems. From our pairwise intraphylum analysis we found that sensory signalling pathways unusually undergo high levels of functional constraint that are higher than genomewide global levels of constraint, and this purifying selection is common within the very divergent taxa we examined. We also find that gene duplication events represent a conserved but heterogeneous driver of evolution within sensory signalling pathways. Taken together, we propose a ‘sessile’ mechanism of sensory signalling pathway evolution, which on one side facilitates bursts of gene duplication and relaxed selection and on the other side it is unusually anchored by high levels of selective constraint that preserves core sensory function

    Cortex, countercurrent context, and dimensional integration of lifetime memory

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    The correlation between relative neocortex size and longevity in mammals encourages a search for a cortical function specifically related to the life-span. A candidate in the domain of permanent and cumulative memory storage is proposed and explored in relation to basic aspects of cortical organization. The pattern of cortico-cortical connectivity between functionally specialized areas and the laminar organization of that connectivity converges on a globally coherent representational space in which contextual embedding of information emerges as an obligatory feature of cortical function. This brings a powerful mode of inductive knowledge within reach of mammalian adaptations, a mode which combines item specificity with classificatory generality. Its neural implementation is proposed to depend on an obligatory interaction between the oppositely directed feedforward and feedback currents of cortical activity, in countercurrent fashion. Direct interaction of the two streams along their cortex-wide local interface supports a scheme of "contextual capture" for information storage responsible for the lifelong cumulative growth of a uniquely cortical form of memory termed "personal history." This approach to cortical function helps elucidate key features of cortical organization as well as cognitive aspects of mammalian life history strategies

    Rank and relevance in novelty and diversity metrics for recommender systems

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    This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in RecSys '11 Proceedings of the fifth ACM conference on Recommender systems, http://dx.doi.org/10.1145/2043932.2043955The Recommender Systems community is paying increasing attention to novelty and diversity as key qualities beyond accuracy in real recommendation scenarios. Despite the raise of interest and work on the topic in recent years, we find that a clear common methodological and conceptual ground for the evaluation of these dimensions is still to be consolidated. Different evaluation metrics have been reported in the literature but the precise relation, distinction or equivalence between them has not been explicitly studied. Furthermore, the metrics reported so far miss important properties such as taking into consideration the ranking of recommended items, or whether items are relevant or not, when assessing the novelty and diversity of recommendations. We present a formal framework for the definition of novelty and diversity metrics that unifies and generalizes several state of the art metrics. We identify three essential ground concepts at the roots of novelty and diversity: choice, discovery and relevance, upon which the framework is built. Item rank and relevance are introduced through a probabilistic recommendation browsing model, building upon the same three basic concepts. Based on the combination of ground elements, and the assumptions of the browsing model, different metrics and variants unfold. We report experimental observations which validate and illustrate the properties of the proposed metrics.This work is supported by the Spanish Government (TIN2011- 28538-C02-01), and the Government of Madrid (S2009TIC-1542)

    Predicting Successful Memes using Network and Community Structure

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    We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.Comment: 10 pages, 6 figures, 2 tables. Proceedings of 8th AAAI Intl. Conf. on Weblogs and social media (ICWSM 2014

    Explicit relevance models in intent-oriented information retrieval diversification

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    This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, http://dx.doi.org/10.1145/2348283.2348297.The intent-oriented search diversification methods developed in the field so far tend to build on generative views of the retrieval system to be diversified. Core algorithm components in particular redundancy assessment are expressed in terms of the probability to observe documents, rather than the probability that the documents be relevant. This has been sometimes described as a view considering the selection of a single document in the underlying task model. In this paper we propose an alternative formulation of aspect-based diversification algorithms which explicitly includes a formal relevance model. We develop means for the effective computation of the new formulation, and we test the resulting algorithm empirically. We report experiments on search and recommendation tasks showing competitive or better performance than the original diversification algorithms. The relevance-based formulation has further interesting properties, such as unifying two well-known state of the art algorithms into a single version. The relevance-based approach opens alternative possibilities for further formal connections and developments as natural extensions of the framework. We illustrate this by modeling tolerance to redundancy as an explicit configurable parameter, which can be set to better suit the characteristics of the IR task, or the evaluation metrics, as we illustrate empirically.This work was supported by the national Spanish projects TIN2011-28538-C02-01 and S2009TIC-1542
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