Path Ranking with Attention to Type Hierarchies

The objective of the knowledge base completion problem is to infer missing information from existing facts in a knowledge base. Prior work has demonstrated the effectiveness of path-ranking based methods, which solve the problem by discovering observable patterns in knowledge graphs, consisting of nodes representing entities and edges representing relations. However, these patterns either lack accuracy because they rely solely on relations or cannot easily generalize due to the direct use of specific entity information. We introduce Attentive Path Ranking, a novel path pattern representation that leverages type hierarchies of entities to both avoid ambiguity and maintain generalization. Then, we present an end-to-end trained attention-based RNN model to discover the new path patterns from data. Experiments conducted on benchmark knowledge base completion datasets WN18RR and FB15k-237 demonstrate that the proposed model outperforms existing methods on the fact prediction task by statistically significant margins of 26% and 10%, respectively. Furthermore, quantitative and qualitative analyses show that the path patterns balance between generalization and discrimination.Comment: Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20

Using Multi-Relational Embeddings as Knowledge Graph Representations for Robotics Applications

User demonstrations of robot tasks in everyday environments, such as households, can be brittle due in part to the dynamic, diverse, and complex properties of those environments. Humans can find solutions in ambiguous or unfamiliar situations by using a wealth of common-sense knowledge about their domains to make informed generalizations. For example, likely locations for food in a novel household. Prior work has shown that robots can benefit from reasoning about this type of semantic knowledge, which can be modeled as a knowledge graph of interrelated facts that define whether a relationship exists between two entities. Semantic reasoning about domain knowledge using knowledge graph representations has improved the robustness and usability of end user robots by enabling more fault tolerant task execution. Knowledge graph representations define the underlying representation of facts, how facts are organized, and implement semantic reasoning by defining the possible computations over facts (e.g. association, fact-prediction). This thesis examines the use of multi-relational embeddings as knowledge graph representations within the context of robust task execution and develops methods to explain the inferences of and sequentially train multi-relational embeddings. This thesis contributes: (i) a survey of knowledge graph representations that model semantic domain knowledge in robotics, (ii) the development and evaluation of our knowledge graph representation based on multi-relational embeddings, (iii) the integration of our knowledge graph representation into a robot architecture to improve robust task execution, (iv) the development and evaluation of methods to sequentially update multi-relational embeddings, and (v) the development and evaluation of an inference reconciliation framework for multi-relational embeddings.Ph.D

Risk-taking and impulsivity; the role of mood states and interoception

Objectives: The consequences of impulsive decisions and actions represent a major source of concern to the health and well-being of individuals and society. It is, therefore, crucial to understand the factors which contribute to impulsive behaviors. Here, we examined how personality traits of behavioral tendencies, interoceptive sensibility as well as transient mood states predict behavioral performance on impulsivity and risk-taking tasks. Method: 574 (121 males; age 18-45) individuals completed self-report personality measures of impulsivity, reward sensitivity, punishment avoidance as well as interoceptive sensibility, undertook a mood assessment and performed a set of cognitive tasks: delay discounting (temporal impulsivity), probability discounting (risk-taking), and reflection impulsivity task. Data were interrogated using principal component analysis, correlations and regression analyses to test mutual relationships between personality traits, interoceptive sensibility, mood state and impulsive behaviors. Results: We observed a clear separation of measures used, both trait and behavioral. Namely, sensation-seeking, reward sensitivity and probability discounting reflected risk-taking. These were separate from measures associated with impulsivity, both trait (negative and positive urgency, premeditation, perseverance) and behavioral (delayed discounting and reflection impulsivity). This separation was further highlighted by their relationship with the current emotional state: positive affect was associated with increased risk-taking tendencies and risky decision-making, while negative emotions were related to heightened impulsivity measures. Interoceptive sensibility was only associated with negative emotions component. Conclusions: Our findings support the proposal that risk-taking and impulsivity represent distinct constructs that are differentially affected by current mood states. This novel insight enhances our understanding of impulsive behaviors

The role of emotions and physiological arousal in modulating impulsive behaviour.

Impulsivity received considerable attention in the context of drug misuse and certain neuropsychiatric conditions. Because of its great health and well-being importance, it is crucial to understand factors which modulate impulsive behaviour. As a growing body of literature indicates the role of emotional and physiological states in guiding our actions and decisions, we argue that current affective state and physiological arousal exert a significant influence on behavioural impulsivity. As 'impulsivity' is a heterogeneous concept, in this paper, we review key theories of the topic and summarise information about distinct impulsivity subtypes and their methods of assessment, pointing out to the differences between the various components of the construct. Moreover, we review existing literature on the relationship between emotional states, arousal and impulsive behaviour and suggest directions for future research

Anxiety and Compulsion Patterns in the Maintenance of Bingeing/Purging

This is the peer reviewed version of the following article: Thomas, M., & Lovell, A. (2014). Anxiety and Compulsion Patterns in the Maintenance of Bingeing/Purging. Journal of Psychiatric and Mental Health Nursing, 22(1), 20-29. DOI: 10.1111/jpm.12167, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jpm.12167/full. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingThis paper reports on the results of a study into the self-reported coping strategies employed by a small sample (n=12) of individuals diagnosed with Bulimia Nervosa purging sub-type, severe and enduring eating disorder (Seed-BN), referred to an out-patient clinic for psychotherapy. Data collection focused on the vomiting activities of participants through analysis of their self-management from diary extracts, which recorded vomiting patterns. Participants all experienced significant mental health issues, had complex histories of BN over a prolonged period, difficulties maintaining relationships, and many had an additional history of substance misuse including dependence on prescription drugs. The study findings indicated two different self-management strategies, anxiety-containment and compulsion-maintenance. There was a clear association between anxiety and controlled weekly vomiting patterns compared with compulsion and daily vomiting patterns. The implications for nursing practice relate to the potential for assessment of differences in vomiting patterns to indicate self-management status and subsequent interventions focusing on either anxiety or compulsive patterns

THE LATE POSITIVE COMPONENT OF EVENT-RELATED BRAIN POTENTIALS AND PERSONALITY.

THE LATE POSITIVE COMPONENT OF EVENT-RELATED BRAIN POTENTIALS AND PERSONALITY