Search results for "generalization"
showing 10 items of 250 documents
Progressive and habitual aspects in Central Mande
2004
This paper examines the marking of progressive and habitual aspects in a cluster of closely related languages (Central Mande) and in a number of dialects in one of these languages (Manding) within the framework of grammaticalization theory. It is shown that the habitual forms go back to a generalization of the progressive aspect and that the progressive forms do derive from locative periphrastic constructions. Furthermore, evidence is provided for the fact that the evolution of progressives in Central Mande occurs in morphological cycles and that the various synchronic progressive constructions can be classified into different layers of grammaticalization. Finally, the consequences of the d…
Suppression of mirror generalization for reversible letters: Evidence from masked priming
2011
Abstract Readers of the Roman script must “unlearn” some forms of mirror generalization when processing printed stimuli (i.e., herb and herd are different words). Here we examine whether the suppression of mirror generalization is a process that affects all letters or whether it mostly affects reversible letters (i.e., b / d ). Three masked priming lexical decision experiments were conducted to examine how the cognitive system processes mirror images of reversible vs. non-reversible letters embedded in Spanish words. Repetition priming effects relative to the mirror-letter condition were substantially greater when the critical letter was reversible (e.g., idea - IDEA vs. ibea - IDEA ) than …
The development of analogy making in children: cognitive load and executive functions.
2010
The aim of the current study was to investigate the performance of 6-, 8-, and 14-year-olds on an analogy-making task involving analogies in which there are competing perceptual and relational matches. We hypothesized that the selection of the common relational structure requires the inhibition of other salient features, in particular, perceptual matches. Using an A:B::C:D paradigm, we showed that children’s performance in analogy-making tasks depends crucially on the nature of the distractors. Children chose more perceptual distractors having a common feature with C compared with A or B (Experiment 1). In addition, they were also influenced by unstructured random textures. When measuring r…
Development of symbolic play through the use of virtual reality tools in children with autistic spectrum disorders: two case studies.
2008
Difficulties in understanding symbolism have been documented as characteristic of autistic spectrum disorders (ASDs). In general, virtual reality (VR) environments offer a set of potential advantages for educational intervention in ASD. In particular, VR offers the advantage, for teaching pretend play and for understanding imagination, of it being possible to show these imaginary transformations explicitly. This article reports two case studies of children with autism (aged 8:6 and 15:7, both male), examining the effectiveness of using a VR tool specifically designed to work on teaching understanding of pretend play. The results, confirmed by independent observers, showed a significant adv…
Becoming a beer expert: is simple exposure with feedback sufficient to learn beer categories?
2015
Category learning is an important aspect of expertise development which had been little studied in the chemosensory field. The wine literature suggests that through repeated exposure to wines, sensory information is stored by experts as prototypes. The goal of this study was to further explore this issue using beers. We tested the ability of beer consumers to correctly categorize beers from two different categories (top- and bottom-fermented beers) before and after repeated exposure with feedback to beers from these categories. We found that participants learned to identify the category membership of beers to which they have been exposed but were unable to generalize their learning to other…
A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes
2011
Published version of an article from the book: Hybrid artificial intelligent systems, Lecture notes in computer science. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-642-21219-2_2 There are numerous applications in Artificial Intelligence (AI) and Machine Learning (ML) where the criteria for decisions are based on testing procedures. The most common tools used in such random phenomena involve Random Walks (RWs). The theory of RWs and its applications have gained an increasing research interest since the start of the last century. [1]. In this context, we note that a RW is, usually, defined as a trajectory involving a series of successive ran…
Do trained assessors generalize their knowledge to new stimuli?
2005
Previous work showed that trained assessors are better at discriminating and describing familiar chemico-sensorial stimuli than novices. In this study, we evaluated whether this superiority holds true for new stimuli. We first trained a group of subjects to characterize beer flavors over a two year period. After training was accomplished, we compared the performance of these trained assessors with the performance of novice subjects for discrimination and matching tasks. The tasks were performed using both well-learned and new beers. Trained assessors outperformed novices in the discrimination task for learned beers but not for new beers. But on the matching task, trained assessors outperfor…
Iterative Reconstruction of Memory Kernels.
2017
In recent years, it has become increasingly popular to construct coarse-grained models with non-Markovian dynamics to account for an incomplete separation of time scales. One challenge of a systematic coarse-graining procedure is the extraction of the dynamical properties, namely, the memory kernel, from equilibrium all-atom simulations. In this article, we propose an iterative method for memory reconstruction from dynamical correlation functions. Compared to previously proposed noniterative techniques, it ensures by construction that the target correlation functions of the original fine-grained systems are reproduced accurately by the coarse-grained system, regardless of time step and disc…
Un procedimiento de fuerte reducción de las dimensiones del RCPS/π
2009
Recently, in the field of project scheduling problems the concept of partially renewable resources has been introduced. Theoretically, it is a generalization of both renewable and non-renewable resources. From an applied point of view, partially renewable resources allow us to model a large variety of situations that do not fit into classical models, but can be found in real problems in timetabling and labour scheduling. When modelling real problems, the problem of project scheduling with partially renewable resources, as many other combinatorial problems, gets such large dimensions that it is quite difficult to apply solution procedures. In this paper, we describe some powerful preprocessi…
A New Min-Max Optimisation Approach for Fast Learning Convergence of Feed-Forward Neural Networks
1993
One of the most critical aspect for a wide use of neural networks to real world problems is related to the learning process which is known to be computational expensive and time consuming.