183 resultados para Declarative


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Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science

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Decision situations are often characterized by uncertainty: we do not know the values of the different options on all attributes and have to rely on information stored in our memory to decide. Several strategies have been proposed to describe how people make inferences based on knowledge used as cues. The present research shows how declarative memory of ACT-R models could be populated based on internet statistics. This will allow to simulate the performance of decision strategies operating on declarative knowledge based on occurrences and co-occurrences of objects and cues in the environment.

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Several studies have documented that emotional arousal may enhance long-term memory. This is an adaptation of a paradigm previously used in North American and European samples in investigations of the influence of emotion on long-term retention. A sample of 46 healthy adults of high and low educational levels watched a slide presentation of stories. A randomly assigned group watched a story with an arousing content and another group watched a neutral story. The stories were matched for structure and comprehensibility and the set and order of the 11 slides were the same in both conditions. Immediately after viewing the slide presentation, the participants were asked to rate the emotionality of the narrative. The arousing narrative was rated as being more emotional than the neutral narrative (t (44) = -3.6, P<0.001). Ten days later subjects were asked to remember the story and answer a multiple-choice questionnaire about it. The subjects who watched the arousing story had higher scores in the free recall measure (t (44) = -2.59, P<0.01). There were no differences between groups in the multiple-choice test of recognition memory (t (44) = 0.26). These findings confirm that an emotional arousing content enhances long-term declarative memory and indicate the possibility of applying this instrument to clinical samples of various cultural backgrounds.

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Sleep spindles have been found to increase following an intense period of learning on a combination of motor tasks. It is not clear whether these changes are task specific, or a result of learning in general. The current study investigated changes in sleep spindles and spectral power following learning on cognitive procedural (C-PM), simple procedural (S-PM) or declarative (DM) learning tasks. It was hypothesized that S-PM learning would result in increases in Sigma power during Non-REM sleep, whereas C-PM and DM learning would not affect Sigma power. It was also hypothesized that DM learning would increase Theta power during REM sleep, whereas S-PM and C-PM learning would not affect Theta power. Thirty-six participants spent three consecutive nights in the sleep laboratory. Baseline polysomnographic recordings were collected on night 2. Participants were randomly assigned to one of four conditions: C-PM, S-PM, DM or control (C). Memory task training occurred on night 3 followed by polysomnographic recording. Re-testing on respective memory tasks occurred one-week following training. EEG was sampled at 256Hz from 16 sites during sleep. Artifact-free EEG from each sleep stage was submitted to power spectral analysis. The C-PM group made significantly fewer errors, the DM group recalled more, and the S-PM improved on performance from test to re-test. There was a significant night by group interaction for the duration of Stage 2 sleep. Independent t-tests revealed that the S-PM group had significantly more Stage 2 sleep on the test night than the C group. The C-PM and the DM group did not differ from controls in the duration of Stage 2 sleep on test night. There was no significant change in the duration of slow wave sleep (SWS) or REM sleep. Sleep spindle density (spindles/minute) increased significantly from baseline to test night following S-PM learning, but not for C-PM, DM or C groups. This is the first study to have shown that the same pattern of results was found for spindles in SWS. Low Sigma power (12-14Hz) increased significantly during SWS following S-PM learning but not for C-PM, DM or C groups. This effect was maximal at Cz, and the largest increase in Sigma power was at Oz. It was also found that Theta power increased significantly during REM sleep following DM learning, but not for S-PM, C-PM or C groups. This effect was maximal at Cz and the largest change in Theta power was observed at Cz. These findings are consistent with the previous research that simple procedural learning is consolidated during Stage 2 sleep, and provide additional data to suggest that sleep spindles across all non-REM stages and not just Stage 2 sleep may be a mechanism for brain plasticity. This study also provides the first evidence to suggest that Theta activity during REM sleep is involved in memory consolidation.

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While sleep has been shown to be involved in memory consolidation and the selective enhancement of newly acquired memories of future relevance (Wilhelm, et al., 2011), limited research has investigated the role of sleep or future relevance in processes of memory reconsolidation. The current research employed a list-method directed forgetting procedure in which participants learned two lists of syllable pairs on Night 1 and received directed forgetting instructions on Night 2. On Night 2, one group (Labile; n = 15) received a memory reactivation treatment consisting of reminders designed to return memories of the learned lists to a labile state. A second group (Stable, n = 16) received similar reminders designed to leave memories of the learned lists in their stable state. No differences in forgetting were found across the two lists or groups. However, a negative correlation between frontal delta (1 – 4 Hz) electroencephalographic (EEG) power during Early Stage 2 non-rapid eye movement (NREM) sleep and forgetting of to-beremembered material was found exclusively in the Labile group (r = -.61, p < .05). Further, central theta (4 – 8 Hz ) EEG power during rapid eye movement (REM) sleep was found to correlate with directed forgetting exclusively in the Labile group (r = .81, p < .001) and total forgetting in the Stable group (r = .50, p < .05). These observed relationships support the proposed hypothesis suggesting that sleep processes are involved in the reconsolidation of labile memories, and that this reconsolidation may be selective for memories of future relevance. A role for sleep in the beneficial reprocessing of memories through the selective reconsolidation of labile memories in NREM sleep and the weakening of memories in REM sleep is discussed.

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The EP2025 EDS project develops a highly parallel information server that supports established high-value interfaces. We describe the motivation for the project, the architecture of the system, and the design and application of its database and language subsystems. The Elipsys logic programming language, its advanced applications, EDS Lisp, and the Metal machine translation system are examined.

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Problematic trace-antecedent relations between deep and surface structure have been a dominant theme in sentence comprehension in agrammatism. We challenge this view and propose that the comprehension in agrammatism in declarative sentences and wh-questions stems from impaired processing in logical form. We present new data from wh-questions and declarative sentences and advance a new hypothesis which we call the set partition hypothesis. We argue that elements that signal set partition operations influence sentence comprehension while trace-antecedent relations remain intact. (C) 2007 Elsevier Ltd. All rights reserved.

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Sleep helps the consolidation of declarative memories in the laboratory, but the pro-mnemonic effect of daytime naps in schools is yet to be fully characterized. While a few studies indicate that sleep can indeed benefit school learning, it remains unclear how best to use it. Here we set out to evaluate the influence of daytime naps on the duration of declarative memories learned in school by students of 10–15 years old. A total of 584 students from 6th grade were investigated. Students within a regular classroom were exposed to a 15-min lecture on new declarative contents, absent from the standard curriculum for this age group. The students were then randomly sorted into nap and non-nap groups. Students in the nap group were conducted to a quiet room with mats, received sleep masks and were invited to sleep. At the same time, students in the non-nap group attended regular school classes given by their usual teacher (Experiment I), or English classes given by another experimenter (Experiment II). These 2 versions of the study differed in a number of ways. In Experiment I (n = 371), students were pre-tested on lecture-related contents before the lecture, were invited to nap for up to 2 h, and after 1, 2, or 5 days received surprise tests with similar content but different wording and question order. In Experiment II (n = 213), students were invited to nap for up to 50 min (duration of a regular class); surprise tests were applied immediately after the lecture, and repeated after 5, 30, or 110 days. Experiment I showed a significant ∼10% gain in test scores for both nap and non-nap groups 1 day after learning, in comparison with pre-test scores. This gain was sustained in the nap group after 2 and 5 days, but in the non-nap group it decayed completely after 5 days. In Experiment II, the nap group showed significantly higher scores than the non-nap group at all times tested, thus precluding specific conclusions. The results suggest that sleep can be used to enhance the duration of memory contents learned in school.

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The advent of distributed and heterogeneous systems has laid the foundation for the birth of new architectural paradigms, in which many separated and autonomous entities collaborate and interact to the aim of achieving complex strategic goals, impossible to be accomplished on their own. A non exhaustive list of systems targeted by such paradigms includes Business Process Management, Clinical Guidelines and Careflow Protocols, Service-Oriented and Multi-Agent Systems. It is largely recognized that engineering these systems requires novel modeling techniques. In particular, many authors are claiming that an open, declarative perspective is needed to complement the closed, procedural nature of the state of the art specification languages. For example, the ConDec language has been recently proposed to target the declarative and open specification of Business Processes, overcoming the over-specification and over-constraining issues of classical procedural approaches. On the one hand, the success of such novel modeling languages strongly depends on their usability by non-IT savvy: they must provide an appealing, intuitive graphical front-end. On the other hand, they must be prone to verification, in order to guarantee the trustworthiness and reliability of the developed model, as well as to ensure that the actual executions of the system effectively comply with it. In this dissertation, we claim that Computational Logic is a suitable framework for dealing with the specification, verification, execution, monitoring and analysis of these systems. We propose to adopt an extended version of the ConDec language for specifying interaction models with a declarative, open flavor. We show how all the (extended) ConDec constructs can be automatically translated to the CLIMB Computational Logic-based language, and illustrate how its corresponding reasoning techniques can be successfully exploited to provide support and verification capabilities along the whole life cycle of the targeted systems.

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Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.

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After almost 10 years from “The Free Lunch Is Over” article, where the need to parallelize programs started to be a real and mainstream issue, a lot of stuffs did happened: • Processor manufacturers are reaching the physical limits with most of their approaches to boosting CPU performance, and are instead turning to hyperthreading and multicore architectures; • Applications are increasingly need to support concurrency; • Programming languages and systems are increasingly forced to deal well with concurrency. This thesis is an attempt to propose an overview of a paradigm that aims to properly abstract the problem of propagating data changes: Reactive Programming (RP). This paradigm proposes an asynchronous non-blocking approach to concurrency and computations, abstracting from the low-level concurrency mechanisms.