Nonmonotonic abductive inductive learning

Inductive Logic Programming (ILP) is concerned with the task of generalising sets of positive and negative examples with respect to background knowledge expressed as logic programs. Negation as Failure (NAF) is a key feature of logic programming which provides a means for nonmonotonic commonsense reasoning under incomplete information. But, so far, most ILP research has been aimed at Horn programs which exclude NAF, and has failed to exploit the full potential of normal programs that allow NAF. By contrast, Abductive Logic Programming (ALP), a related task concerned with explaining observations with respect to a prior theory, has been well studied and applied in the context of normal logic programs. This paper shows how ALP can be used to provide a semantics and proof procedure for nonmonotonic ILP that utilises practical methods of language and search bias to reduce the search space. This is done by lifting an existing method called Hybrid Abductive Inductive Learning (HAIL) from Horn clauses to normal logic programs. To demonstrate its potential benefits, the resulting system, called XHAIL, is applied to a process modelling case study involving a nonmonotonic temporal Event Calculus (EC).     

Writing and reading skills as assessed by teachers in 7-year olds: A behavioral genetic approach

A behavioral genetic analysis of general writing ability was conducted using teacher assessments based on UK National Curriculum criteria for a sample of 3296 same-sex pairs of 7-year-old twins. Writing was highly heritable within the normal range (0.66) and at the low extreme (0.70). Environmental influences were almost all non-shared, with shared environmental estimates negligible (0.07 normal range, 0.06 low extreme). Bivariate genetic analyses of teacher assessments of writing and reading indicated that 69% of the genetic influences on writing were in common with those on reading, and that the two skills shared all of their shared environmental influences. In contrast, non-shared environmental factors are largely specific, with 86% independent of those on reading.     

An investigation into the temporal dimension of the Mozart effect: evidence from the attentional blink task

In the present study, we examined whether the 'Mozart effect' would influence participants' temporal attention using a visual attentional blink (AB) task that provides a reliable measure of the temporal dynamics of visual attention. The 'Mozart effect' refers to the specific claim that listening to Mozart's Sonata for Two Pianos in D Major, K.448 can improve the performance in spatio-temporal tasks. Participants had to try and identify two target digits (in their correct order of presentation) presented amongst a stream of distractor letters in three different conditions (presented in separate blocks of trials): while listening to the Mozart sonata played normally, while listening to the same Mozart sonata played in reverse, and while in silence. The results showed that the participants were able to detect the second target (T2) significantly more accurately (given the correct detection of the first target, T1) in the AB stream when the Mozart sonata was played normally than in either of the other two conditions. Possible explanations for the differential effects of Mozart's music being played normally and in reverse and potential confounds in previous studies reporting a facilitatory 'Mozart effect' are discussed. Our results therefore provide the first empirical demonstration supporting the existence of a purely temporal component to the 'Mozart effect' using a non-spatial visual AB task.     

Individual differences in components of reaction time distributions and their relations to working memory and intelligence

The authors bring together approaches from cognitive and individual differences psychology to model characteristics of reaction time distributions beyond measures of central tendency. Ex-Gaussian distributions and a diffusion model approach are used to describe individuals' reaction time data. The authors identified common latent factors for each of the 3 ex-Gaussian parameters and for 3 parameters central to the diffusion model using structural equation modeling for a battery of choice reaction tasks. These factors had differential relations to criterion constructs. Parameters reflecting the tail of the distribution (i.e., tau in the ex-Gaussian and drift rate in the diffusion model) were the strongest unique predictors of working memory, reasoning, and psychometric speed. Theories of controlled attention and binding are discussed as potential theoretical explanations.     

Getting a grip on numbers: numerical magnitude priming in object grasping

To investigate the functional connection between numerical cognition and action planning, the authors required participants to perform different grasping responses depending on the parity status of Arabic digits. The results show that precision grip actions were initiated faster in response to small numbers, whereas power grips were initiated faster in response to large numbers. Moreover, analyses of the grasping kinematics reveal an enlarged maximum grip aperture in the presence of large numbers. Reaction time effects remained present when controlling for the number of fingers used while grasping but disappeared when participants pointed to the object. The data indicate a priming of size-related motor features by numerals and support the idea that representations of numbers and actions share common cognitive codes within a generalized magnitude system.     

Abductive reasoning in neural-symbolic systems

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration.

Impact of Terrorism, Insurgency, and Other Human-caused Catastrophes on Pivotal National Leaders’ Vision Statements

Vision statements articulated by seven pivotal national leaders before and after a catastrophe were examined for changes in moral reasoning stage, moral reasoning orientation, explanatory style, and rumination. Established two-stage structured content analysis methods were used and a perspective of shared leadership. Five leaders showed no significant change in moral reasoning stage but two showed a statistically significant reduction following overt attack on their homeland. After a catastrophe, six showed significant change in moral reasoning orientation, four showed less positive or negative explanatory style, and all seven showed high rumination. From an organizational systems perspective, an impact of human-caused catastrophe was adjustment of these four variables in pivotal national leaders’ vision statements as if they are systems levers.