Additivity Pretraining and cue competition effects: Developmental evidence for a reasoning account of causal learning

The effect of additivity pretraining on blocking has been taken as evidence for a reasoning account of human and animal causal learning. If inferential reasoning underpins this effect, then developmental differences in the magnitude of this effect in children would be expected. Experiment 1 examined cue competition effects in children's (4- to 5-year-olds and 6- to 7-year-olds) causal learning using a new paradigm analogous to the food allergy task used in studies of human adult causal learning. Blocking was stronger in the older than the younger children, and additivity pretraining only affected blocking in the older group. Unovershadowing was not affected by age or by pretraining. In experiment 2, levels of blocking were found to be correlated with the ability to answer questions that required children to reason about additivity. Our results support an inferential reasoning explanation of cue competition effects. (c) 2012 APA, all rights reserved.

Children’s Reasoning About the Temporal Order of Past and Future Events

Four- and five-year-olds completed two sets of tasks that involved reasoning about the temporal order in which events had occurred in the past or were to occur in the future. Four-year-olds succeeded on the tasks that involved reasoning about the order of past events but not those that involved reasoning about the order of future events, whereas 5-year-olds passed both types of tasks. Individual children who failed the past-event tasks were not particularly likely to fail the more difficult future-event tasks. However, children's performance on the reasoning tasks was predictive of their performance on a task assessing their comprehension of the terms “before” and “after.” Our results suggest that there may be a developmental change over this age range in the ability to flexibly represent and reason about the before-and-after relationships between events.

Emotional intelligence, personality and decoding non-verbal expressions of emotion

Previous research has highlighted theoretical and empirical links between measures of both personality and trait emotional intelligence (EI), and the ability to decode facial expressions of emotion. Research has also found that the posed, static characteristics of the photographic stimuli used to explore these links affects the decoding process and differentiates them from the natural expressions they represent. This undermines the ecological validity of established trait-emotion decoding relationships. This study addresses these methodological shortcomings by testing relationships between the reliability of participant ratings of dynamic, spontaneously elicited expressions of emotion with personality and trait EI. Fifty participants completed personality and self-report EI questionnaires, and used a computer-logging program to continuously rate change in emotional intensity expressed in video clips. Each clip was rated twice to obtain an intra-rater reliability score. The results provide limited support for links between both trait EI and personality variables and how reliably we decode natural expressions of emotion. Limitations and future directions are discussed.

This is Not a Photo Opportunity: Verbal/Visual Struggle in Francophone Travel Narratives

This article explores the ethics and aesthetics of representing travel and intercultural encounter in textual and photographic forms. Taking as its starting point two textual accounts of journeys in the course of which photographic narratives were also produced, the article explores the possibilities and limitations of textuality and visuality and thus considers the implications of, or new opportunities afforded by, reading – and ultimately publishing – these narratives as iconotexts. Focusing on Pierre Loti's L'Inde (sans les Anglais) (1901) and Ella Maillart's Oasis interdites (1937), the article also offers an alternative perspective on writers whose work is commonly associated with an imperialist or exoticist discourse, with cliché and one-dimensionality. As such, it aims to replace the monolithic, orientalist vision often attributed to these writers with ambiguity, ethical hesitation and a plurality of perspectives. Using these examples as a springboard, the article seeks to argue that verbal/visual mobility in narratives representing mobility contributes to resisting static, monolithic perceptions of other cultures. Using the work of British graffiti artist Banksy as a foil for exploring photography as cultural commodification and art as commodity, the article also seeks to engage with current debates in Humanities research on ekphrasis and iconotextuality and on the problematics of representing other cultures within an ethical and/or humanist frame.

The role of ECE1 variants in cognitive ability in old age and Alzheimer's disease risk

The ß-amyloid peptide may play a central role in Alzheimer's disease (AD) pathogenesis. We have evaluated variants in seven Aß-degrading genes (ACE, ECE1, ECE2, IDE, MME, PLAU, and TF) for association with AD risk in the Genetic and Environmental Risk in Alzheimer's Disease Consortium 1 (GERAD1) cohort, and with three cognitive phenotypes in the Lothian Birth Cohort 1936 (LBC1936), using 128 and 121 SNPs, respectively. In GERAD1, we identified a significant association between a four-SNP intragenic ECE1 haplotype and risk of AD in individuals that carried at least one APOE e4 allele (P = 0.00035, odds ratio = 1.61). In LBC1936, we identified a significant association between a different two-SNP ECE1 intragenic haplotype and non-verbal reasoning in individuals lacking the APOE e4 allele (P = 0.00036, ß = -0.19). Both results showed a trend towards significance after permutation (0.05 <P <0.10). A follow-up cognitive genetic study evaluated the association of ECE1 SNPs in three additional cohorts of non-demented older people. Meta-analysis of the four cohorts identified the significant association (Z <0.05) of SNPs in the ECE-1b promoter with non-verbal reasoning scores, particularly in individuals lacking the APOE e4 allele. Our genetic findings are not wholly consistent. Nonetheless, the AD associated intronic haplotype is linked to the 338A variant of known ECE1b promoter variant, 338C>A (rs213045). We observed significantly less expression from the 338A variant in two human neuroblastoma cell lines and speculate that this promoter may be subject to tissue-specific regulation.

Logic feels so good-I like it! Evidence for intuitive detection of logicality in syllogistic reasoning

When people evaluate syllogisms, their judgments of validity are often biased by the believability of the conclusions of the problems. Thus, it has been suggested that syllogistic reasoning performance is based on an interplay between a conscious and effortful evaluation of logicality and an intuitive appreciation of the believability of the conclusions (e.g., Evans, Newstead, Allen, & Pollard, 1994). However, logic effects in syllogistic reasoning emerge even when participants are unlikely to carry out a full logical analysis of the problems (e.g., Shynkaruk & Thompson, 2006). There is also evidence that people can implicitly detect the conflict between their beliefs and the validity of the problems, even if they are unable to consciously produce a logical response (e.g., De Neys, Moyens, & Vansteenwegen, 2010). In 4 experiments we demonstrate that people intuitively detect the logicality of syllogisms, and this effect emerges independently of participants' conscious mindset and their cognitive capacity. This logic effect is also unrelated to the superficial structure of the problems. Additionally, we provide evidence that the logicality of the syllogisms is detected through slight changes in participants' affective states. In fact, subliminal affective priming had an effect on participants' subjective evaluations of the problems. Finally, when participants misattributed their emotional reactions to background music, this significantly reduced the logic effect.

A defeasible reasoning model of inductive concept learning from examples and communication

This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a preference relation on inductive theories we can characterize the inductive bias of ICL algorithms. The second part of the paper shows how this logical characterization of inductive generalization can be integrated with another form of non-monotonic reasoning (argumentation), to define a model of multiagent ICL. This integration allows two or more agents to learn, in a consistent way, both from induction and from arguments used in the communication between them. We show that the inductive theories achieved by multiagent induction plus argumentation are sound, i.e. they are precisely the same as the inductive theories built by a single agent with all data. © 2012 Elsevier B.V.

Adaptive Dialogue Strategy Selection through Imprecise Probabilistic Query Answering

In a human-computer dialogue system, the dialogue strategy can range from very restrictive to highly flexible. Each specific dialogue style has its pros and cons and a dialogue system needs to select the most appropriate style for a given user. During the course of interaction, the dialogue style can change based on a user’s response and the system observation of the user. This allows a dialogue system to understand a user better and provide a more suitable way of communication. Since measures of the quality of the user’s interaction with the system can be incomplete and uncertain, frameworks for reasoning with uncertain and incomplete information can help the system make better decisions when it chooses a dialogue strategy. In this paper, we investigate how to select a dialogue strategy based on aggregating the factors detected during the interaction with the user. For this purpose, we use probabilistic logic programming (PLP) to model probabilistic knowledge about how these factors will affect the degree of freedom of a dialogue. When a dialogue system needs to know which strategy is more suitable, an appropriate query can be executed against the PLP and a probabilistic solution with a degree of satisfaction is returned. The degree of satisfaction reveals how much the system can trust the probability attached to the solution.

Integrating textual analysis and evidential reasoning for decision making in Engineering design

Decision making is an important element throughout the life-cycle of large-scale projects. Decisions are critical as they have a direct impact upon the success/outcome of a project and are affected by many factors including the certainty and precision of information. In this paper we present an evidential reasoning framework which applies Dempster-Shafer Theory and its variant Dezert-Smarandache Theory to aid decision makers in making decisions where the knowledge available may be imprecise, conflicting and uncertain. This conceptual framework is novel as natural language based information extraction techniques are utilized in the extraction and estimation of beliefs from diverse textual information sources, rather than assuming these estimations as already given. Furthermore we describe an algorithm to define a set of maximal consistent subsets before fusion occurs in the reasoning framework. This is important as inconsistencies between subsets may produce results which are incorrect/adverse in the decision making process. The proposed framework can be applied to problems involving material selection and a Use Case based in the Engineering domain is presented to illustrate the approach. © 2013 Elsevier B.V. All rights reserved.

Language development at 3 years in pre-term children of birth weight below 1000 g

Language development at 3 years of pre-term children born below 1000 g birth weight was compared with full-term controls matched for social background. The pre-term group used less complex expressive language and showed lower receptive understanding, auditory memory and verbal reasoning. Language outcome was related to intraventricular haemorrhage but not to global indication of postnatal illness such as number of days on the ventilator. Average verbal intelligence in environmentally low risk, extremely low birth weight children is an insufficient indicator of complex language functioning.

Diachronic Change in Verbal Agreement Patterns with Majorité

This article is concerned with the description of data relating to a case of morphosyntactic variation and change in French: verbal agreement patterns with the noun majorité (‘majority’). Quantitative analysis of apparent-time data from cloze (‘gap-fill’) tests suggests that plural agreement with this noun is increasing; data from a diachronic corpus study confirm that this is the case. A number of factors are found to constrain this variation and change, including most importantly the presence and number of a post-modifying noun phrase (e.g. la majorité des hommes). The implications of these findings for the definition of collective nouns in French are discussed.

Common-sense reasoning for human action recognition

This paper presents a novel method that leverages reasoning capabilities in a computer vision system dedicated to human action recognition. The proposed methodology is decomposed into two stages. First, a machine learning based algorithm - known as bag of words - gives a first estimate of action classification from video sequences, by performing an image feature analysis. Those results are afterward passed to a common-sense reasoning system, which analyses, selects and corrects the initial estimation yielded by the machine learning algorithm. This second stage resorts to the knowledge implicit in the rationality that motivates human behaviour. Experiments are performed in realistic conditions, where poor recognition rates by the machine learning techniques are significantly improved by the second stage in which common-sense knowledge and reasoning capabilities have been leveraged. This demonstrates the value of integrating common-sense capabilities into a computer vision pipeline. © 2012 Elsevier B.V. All rights reserved.

Web Services and Incerta Spiriti: A Game Theoretic Approach to Uncertainty

A web-service is a remote computational facility which is made available for general use by means of the internet. An orchestration is a multi-threaded computation which invokes remote services. In this paper game theory is used to analyse the behaviour of orchestration evaluations when underlying web-services are unreliable. Uncertainty profiles are proposed as a means of defining bounds on the number of service failures that can be expected during an orchestration evaluation. An uncertainty profile describes a strategic situation that can be analyzed using a zero-sum angel-daemon game with two competing players: an angel a whose objective is to minimize damage to an orchestration and a daemon d who acts in a destructive fashion. An uncertainty profile is assessed using the value of its angel daemon game. It is shown that uncertainty profiles form a partial order which is monotonic with respect to assessment.