Boundaries and Prototypes in Categorizing Direction

Projective terms such as left, right, front, back are conceptually interesting due to their flexibility of contextual usage and their central relevance to human spatial cognition. Their default acceptability areas are well known, with prototypical axes representing their most central usage and decreasing acceptability away from the axes. Previous research has shown these axes to be boundaries in certain non-linguistic tasks, indicating an inverse relationship between linguistic and non-linguistic direction concepts under specific circumstances. Given this striking mismatch, our study asks how such inverse non-linguistic concepts are represented in language, as well as how people describe their categorization. Our findings highlight two distinct grouping strategies reminiscent of theories of human categorization: prototype based or boundary based. These lead to different linguistic as well as non-linguistic patterns

Phenomenological Psychopathology and Psychiatric Classification

In this chapter, I provide an overview of phenomenological approaches to psychiatric classification. My aim is to encourage and facilitate philosophical debate over the best ways to classify psychiatric disorders. First, I articulate phenomenological critiques of the dominant approach to classification and diagnosis—i.e., the operational approach employed in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and the International Classification of Diseases (ICD-10). Second, I describe the type or typification approach to psychiatric classification, which I distinguish into three different versions: ideal types, essential types, and prototypes. I argue that despite their occasional conflation in the contemporary literature, there are important distinctions among these approaches. Third, I outline a new phenomenological-dimensional approach. I show how this approach, which starts from basic dimensions of human existence, allows us to investigate the full range of psychopathological conditions without accepting the validity of current diagnostic categories

A prototypical approach to machine learning

This paper presents an overview of a research programme on machine learning which is based on the fundamental process of categorization. This work draws upon the psychological theory of prototypical concepts . This theory is that concepts learnt naturally from interaction with the environment (basic categories) are not structured or defined in logical terms but are clustered in accordance with their similaritry to a central prototype, representing the "most typical" member. A structure of a computer model designed to achieve categorization is outlined and the knowledge representational forms and developmental learning associated with this approach are discussed

Sense and symbolic objects: Strategic sensemaking through design

This paper reports on an ongoing investigation into one aspect of the design thinking phenomenon, namely the use of designed artifacts — sketches, renderings, graphics, models and prototypes — as symbolic objects in strategy making and implementation. It examines the conceptual overlap between design and the strategic cognition perspective, which considers cognitive processes and structures involved in strategic decision making, particularly the phenomenon of sensemaking. It is primarily a theoretical exploration, but draws on two short testimonies from designers. The specific conceptual connection between design practice and strategic cognition theory is potentially valuable to business leaders and managers involved with innovation, design management and strategic decisions. Preliminary findings suggest sensemaking activities by designers generate innovative future concepts with far-reaching strategic implications; designed artifacts aid sensemaking and sensegiving by management in exploring new business opportunities and directions. This paper is an early draft of a fuller account to be published in 2013 (AIEDAM Special Issue, Spring 2013, Vol.27, No.2, Studying and Supporting Design Communication, Edited by: Maaike Kleinsmann & Anja Maier)

Design as communication in micro-strategy — strategic sensemaking and sensegiving mediated through designed artefacts.

This paper relates key concepts of strategic cognition in microstrategy to design practice. It considers the potential roles of designers' output in strategic sensemaking and sensegiving. Designed artifacts play well-known roles as communication media; sketches, renderings, models, and prototypes are created to explore and test possibilities and to communicate these options within and outside the design team. This article draws on design and strategy literature to propose that designed artifacts can and do play a role as symbolic communication resources in sensemaking and sensegiving activities that impact strategic decision making and change. Extracts from interviews with three designers serve as illustrative examples. This article is a call for further empirical exploration of such a complex subject

Interpretable Categorization of Heterogeneous Time Series Data

Understanding heterogeneous multivariate time series data is important in many applications ranging from smart homes to aviation. Learning models of heterogeneous multivariate time series that are also human-interpretable is challenging and not adequately addressed by the existing literature. We propose grammar-based decision trees (GBDTs) and an algorithm for learning them. GBDTs extend decision trees with a grammar framework. Logical expressions derived from a context-free grammar are used for branching in place of simple thresholds on attributes. The added expressivity enables support for a wide range of data types while retaining the interpretability of decision trees. In particular, when a grammar based on temporal logic is used, we show that GBDTs can be used for the interpretable classi cation of high-dimensional and heterogeneous time series data. Furthermore, we show how GBDTs can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply GBDTs to analyze the classic Australian Sign Language dataset as well as data on near mid-air collisions (NMACs). The NMAC data comes from aircraft simulations used in the development of the next-generation Airborne Collision Avoidance System (ACAS X).Comment: 9 pages, 5 figures, 2 tables, SIAM International Conference on Data Mining (SDM) 201

Categorization in Real-World Tasks

We examine the role of category representations for decision-making in real-life tasks. To this end, we empirically examine how people categorize kitchen objects and make use of categories when storing objects in a kitchen. We then compare two computational models and their ability to represent the participants’ mental models. We discuss the advantages and disadvantages of the models and point the way to further researc

STAR framework revisited: Curriculum for user-centered design summer schools

Annually, an interdisciplinary community of students, researchers and practitioners from computer engineering, social sciences, Human Computer Interaction, visual communication and other related disciplines, gather together for 2-to-5 weeks to participate in intensive summer school sessions. Although the overall theme and the participants vary each year, these programs remain focused on the teaching and practice of User-Centered Design (UCD) in the context of the local community where the academy is conducted. By listening to lectures, working in ateliers, living with target users and facing real-world design problems, participants experientially learn a mixture of IxD processes, ethnographic methods, prototyping techniques and teamwork skills, despite the program's short duration. Intensive design summer academies like this are essential, as they offer an environment for experimentation that is difficult to create in other educational settings. However, organizing and implementing these programs in ways that optimize the learning process is challenging. As past participants, atelier leaders and instructors for a variety of summer workshops, the authors made several poignant observations about the need for an educational framework to facilitate learning and to address the students' diverse cultural backgrounds, educational disciplines, learning techniques and cultural markers. Upon further examination of the educational literature, ethnographic observation during subsequent summer sessions and interviews of past students, atelier leaders, lecturers and organizers, the authors proposed the STAR Framework for design summer schools. [see Schadewitz, Adler, Moncur, Roberts, 2006] While this framework offers organizers clear direction on structuring IxD summer schools, it provides little guidance on the curriculum itself. It has become clear that special attention must also be paid to the content, order and delivery of the curriculum, particularly given the limited time frame of the session. Building upon the established framework, this paper proposes a curricular construct that will maximize knowledge transfer within the summer school context

The Self-Organization of Speech Sounds

The speech code is a vehicle of language: it defines a set of forms used by a community to carry information. Such a code is necessary to support the linguistic interactions that allow humans to communicate. How then may a speech code be formed prior to the existence of linguistic interactions? Moreover, the human speech code is discrete and compositional, shared by all the individuals of a community but different across communities, and phoneme inventories are characterized by statistical regularities. How can a speech code with these properties form? We try to approach these questions in the paper, using the ``methodology of the artificial''. We build a society of artificial agents, and detail a mechanism that shows the formation of a discrete speech code without pre-supposing the existence of linguistic capacities or of coordinated interactions. The mechanism is based on a low-level model of sensory-motor interactions. We show that the integration of certain very simple and non language-specific neural devices leads to the formation of a speech code that has properties similar to the human speech code. This result relies on the self-organizing properties of a generic coupling between perception and production within agents, and on the interactions between agents. The artificial system helps us to develop better intuitions on how speech might have appeared, by showing how self-organization might have helped natural selection to find speech