14,215 research outputs found
The Ouroboros Model
At the core of the Ouroboros Model lies a self-referential recursive process with alternating phases of data acquisition and evaluation. Memory entries are organized in schemata. Activation at a time of part of a schema biases the whole structure and, in particular, missing features, thus triggering expectations. An iterative recursive monitor process termed âconsumption analysisâ is then checking how well such expectations fit with successive activations. A measure for the goodness of fit, âemotionâ, provides feedback as (self-) monitoring signal. Contradictions between anticipations based on previous experience and actual current data are highlighted as well as minor gaps and deficits. The basic algorithm can be applied to goal directed movements as well as to abstract rational reasoning when weighing evidence for and against some remote theories. A sketch is provided how the Ouroboros Model can shed light on rather different characteristics of human behavior including learning and meta-learning. Partial implementations proved effective in dedicated safety systems
Implicit learning of recursive context-free grammars
Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning
experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have
not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing
features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured
the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both
distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes
even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between
individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for
tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex
context-free structures, which model some features of natural languages. They support the relevance of artificial grammar
learning for probing mechanisms of language learning and challenge existing theories and computational models of
implicit learning
Attitudes expressed in online comments about environmental factors in the tourism sector: an exploratory study
The object of this exploratory study is to identify the positive, neutral and negative
environment factors that affect users who visit Spanish hotels in order to help the hotel managers
decide how to improve the quality of the services provided. To carry out the research a Sentiment
Analysis was initially performed, grouping the sample of tweets (n = 14459) according to the feelings
shown and then a textual analysis was used to identify the key environment factors in these feelings
using the qualitative analysis software Nvivo (QSR International, Melbourne, Australia). The results
of the exploratory study present the key environment factors that affect the users experience when
visiting hotels in Spain, such as actions that support local traditions and products, the maintenance of
rural areas respecting the local environment and nature, or respecting air quality in the areas where
hotels have facilities and offer services. The conclusions of the research can help hotels improve their
services and the impact on the environment, as well as improving the visitors experience based on
the positive, neutral and negative environment factors which the visitors themselves identified
A context-sensitive conceptual framework for activity modeling
Human motion trajectories, however captured, provide a rich spatiotemporal data source for human activity recognition, and the rich literature in motion trajectory analysis provides the tools to bridge the gap between this data and its semantic interpretation. But activity is an ambiguous term across research communities. For example, in urban transport research activities are generally characterized around certain locations assuming the opportunities and resources are present in that location, and traveling happens between these locations for activity participation, i.e., travel is not an activity, rather a mean to overcome spatial constraints. In contrast, in human-computer interaction (HCI) research and in computer vision research activities taking place along the way, such as reading on the bus, are significant for contextualized service provision. Similarly activities at coarser spatial and temporal granularity, e.g., holidaying in a country, could be recognized in some context or domain. Thus the context prevalent in the literature does not provide a precise and consistent definition of activity, in particular in differentiation to travel when it comes to motion trajectory analysis. Hence in this paper, a thorough literature review studies activity from different perspectives, and develop a common framework to model and reason human behavior flexibly across contexts. This spatio-temporal framework is conceptualized with a focus on modeling activities hierarchically. Three case studies will illustrate how the semantics of the term activity changes based on scale and context. They provide evidence that the framework holds over different domains. In turn, the framework will help developing various applications and services that are aware of the broad spectrum of the term activity across contexts
From holism to compositionality: memes and the evolution of segmentation, syntax, and signification in music and language
Steven Mithen argues that language evolved from an antecedent he terms âHmmmmm, [meaning it was] Holistic, manipulative, multi-modal, musical and mimeticâ. Owing to certain innate and learned factors, a capacity for segmentation and cross-stream mapping in early Homo sapiens broke the continuous line of Hmmmmm, creating discrete replicated units which, with the initial support of Hmmmmm, eventually became the semantically freighted words of modern language. That which remained after what was a bifurcation of Hmmmmm arguably survived as music, existing as a sound stream segmented into discrete units, although one without the explicit and relatively fixed semantic content of language. All three types of utterance â the parent Hmmmmm, language, and music â are amenable to a memetic interpretation which applies Universal Darwinism to what are understood as language and musical memes. On the basis of Peter Carruthersâ distinction between âcognitivismâ and âcommunicativismâ in language, and William Calvinâs theories of cortical information encoding, a framework is hypothesized for the semantic and syntactic associations between, on the one hand, the sonic patterns of language memes (âlexemesâ) and of musical memes (âmusemesâ) and, on the other hand, âmentaleseâ conceptual structures, in Chomskyâs âLogical Formâ (LF)
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