Hume's Legacy: A Cognitive Science Perspective

Hume is an experimental philosopher who attempts to understand why we think, feel, and act as we do. But how should we evaluate the adequacy of his proposals? This chapter examines Hume’s account from the perspective of interdisciplinary work in cognitive science

Clear Visual Separation of Temporal Event Sequences

Extracting and visualizing informative insights from temporal event sequences becomes increasingly difficult when data volume and variety increase. Besides dealing with high event type cardinality and many distinct sequences, it can be difficult to tell whether it is appropriate to combine multiple events into one or utilize additional information about event attributes. Existing approaches often make use of frequent sequential patterns extracted from the dataset, however, these patterns are limited in terms of interpretability and utility. In addition, it is difficult to assess the role of absolute and relative time when using pattern mining techniques. In this paper, we present methods that addresses these challenges by automatically learning composite events which enables better aggregation of multiple event sequences. By leveraging event sequence outcomes, we present appropriate linked visualizations that allow domain experts to identify critical flows, to assess validity and to understand the role of time. Furthermore, we explore information gain and visual complexity metrics to identify the most relevant visual patterns. We compare composite event learning with two approaches for extracting event patterns using real world company event data from an ongoing project with the Danish Business Authority.Comment: In Proceedings of the 3rd IEEE Symposium on Visualization in Data Science (VDS), 201

'Sounds of Intent' : Mapping musical behaviour and development in children and young people with complex needs

This article reports on the first year of an Esmae Fairbairn Foundation-funded research project into the design and evaluation of an original 'framework' for mapping the behaviour and development in, and through, music for children with complex needs, specifically those with profound and multiple learning difficulties (PMLD). An initial four-month design and pilot phase critiqued and evaluated a framework that was grounded in video-based iterative analyses of individual case studies that had been collected during the previous two years. The piloting phase was followed by a sustained period of classroom-based music lesson observation in five special schools over a period of seven months. A total of 630 observations were made using the framework for 68 participants whose ages ranged from 4 years 7 months to 19 years 1 month. Subsequent analyses support the general design features of the observational framework and provide new evidence of PMLD musical behaviour and development

A half century of progress towards a unified neural theory of mind and brain with applications to autonomous adaptive agents and mental disorders

Invited article for the book Artificial Intelligence in the Age of Neural Networks and Brain Computing R. Kozma, C. Alippi, Y. Choe, and F. C. Morabito, Eds. Cambridge, MA: Academic PressThis article surveys some of the main design principles, mechanisms, circuits, and architectures that have been discovered during a half century of systematic research aimed at developing a unified theory that links mind and brain, and shows how psychological functions arise as emergent properties of brain mechanisms. The article describes a theoretical method that has enabled such a theory to be developed in stages by carrying out a kind of conceptual evolution. It also describes revolutionary computational paradigms like Complementary Computing and Laminar Computing that constrain the kind of unified theory that can describe the autonomous adaptive intelligence that emerges from advanced brains. Adaptive Resonance Theory, or ART, is one of the core models that has been discovered in this way. ART proposes how advanced brains learn to attend, recognize, and predict objects and events in a changing world that is filled with unexpected events. ART is not, however, a “theory of everything” if only because, due to Complementary Computing, different matching and learning laws tend to support perception and cognition on the one hand, and spatial representation and action on the other. The article mentions why a theory of this kind may be useful in the design of autonomous adaptive agents in engineering and technology. It also notes how the theory has led to new mechanistic insights about mental disorders such as autism, medial temporal amnesia, Alzheimer’s disease, and schizophrenia, along with mechanistically informed proposals about how their symptoms may be ameliorated

An emergence perspective on entrepreneurship: processes, structure and methodology

This paper explores entrepreneurship from the perspective of emergence, drawing on literature in complexity theory, social theory and entrepreneurship. Entrepreneurship is conceptualised as the production of emergence, or emergent properties, via a simple model of initial conditions, processes of emergence that produces emergent properties at multiple levels (new phenomena such as products, services, firms, networks, patterns of behaviour, identities). Conceptualisation through emergence thus embraces actors, context, processes and (structural) outcomes. This paper builds on previous work that theorises the relationship between entrepreneurship and social change. We extend that work by considering the methodological implications of relating processes of entrepreneurship to the emergence of new phenomena