This page will be updated as more information about the invited speakers and their talks becomes available.
Erik Altmann is a post-doctoral researcher working with Wayne Gray at the Krasnow Institute for Advanced Studies at George Mason University, just outside of Washington, DC, USA.
Invited talk: Mechanisms and implications of pervasive episodic memory
An examination of real-world tasks suggests that people encode a vast
amount of fine-grain episodic information automatically in long-term
memory. I will discuss a computational cognitive model of one such
task that involves a computer user remembering and finding
previously-displayed information. Constraints on the model will be
traced back to the task and data and to the cognitive architecture in
which the model is implemented (Soar). With these constraints in
place, implications will be drawn for HCI and psychology. These
include perspectives on the cost of a cluttered interface, on the role
of background knowledge in gaining access to ephemeral detail, and on
episodic representations necessary to support simple reality
monitoring.
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invited speakers.
René Amalberti is a research professor at IMASSA, the Institute of Aerospace Medicine of the French Department of Defence, where he is deputy head of the Department of Cognitive Sciences and Ergonomics. He researches into the user modelling aspects of aviation, including those concerning flight automation. He is also attached part-time to DGAC, the Directorate General of Civil Aviation of the French Ministry of Transport, where he leads the group on human factors. He chairs the European Human Factors steering group of the Joint Aviation Authorities to prepare future human factors regulations. He can be reached at: rene-a@imaginet.fr .
Invited talk: Why Operators' Cognitive Models are Hard to Incorporate into Design: The Case of Human Reliability Models
Operators' models, or equivalent end-user models, have became a standard prerequisite for most man-machine system design. Nowadays, the designer can chose among a great variety of models: behavioral models of performance, running competence models, and cognitive models are available in a large range of granularity from quasi-neuropsychological models of memory to framework models of dynamic cognition. However, despite -- or maybe because of -- that variety, modelling the operator is still an area of uncertainty within the industry, with multiple forms and meanings, and with a persistent feeling that these models, whereas they should be useful, are hard to incorporate into the design process.
This paper focuses on the development and use of cognitive models of human reliability for the design of complex systems, and tries to understand biases and limitations of their use within the industry. In that sense, the paper is more industry-oriented than research oriented. It is divided into three sections. The first section details the range of existing cognitive models of human reliability and proposes a classification of these models into four main categories: error production models, error detection and recovery models, systemic models, and integrated safety ecological models. The example of the Aviation Industry shows how difficult it has been in the recent past to incorporate the most advanced of these models into design, whereas the same Industry had long complained about the lack of availabilily of cognitive operators' models.
The second section tries to explain the reason for the relative failure. It shows the inter-dependency existing between the category of cognitive model, the safety paradigm, and the strategy for design. Severe drawbacks may occur each time a model is used with the wrong safety paradigm or the wrong strategy for design. It also shows that the more cognitively-based the model is, the less it is incorporated into design. The lack of education in psychology of designers, as well as the lack of a clear procedure for incorporating such models into design, are among the most important factors explaining this lack of success.
The third and last section points to new directions in cognitive modelling
to improve the fit between operator modelling and design requirements.
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Marcel Just researches and teaches in cognition and cognitive neuroscience in the Psychology Department at Carnegie Mellon University, Pittsburgh, USA.
Invited talk: Modeling Neural Function and High Level Cognition
Recent brain imaging findings suggest several new assumptions concerning the architectural properties of the neural systems that underlie high level cognition, such as language, comprehension, visual cognition, and problem solving. Some of these assumptions have to do with
The 4CAPS computational modeling system implements these assumptions, with
the goal of accounting not only for processing times and error
probabilities, but also for the amount of brain activation observed in each
of the activated component neural systems. 4CAPS consists of several
component processing modules, each of which is a parallel production system
with some connectionist properties, and each of which is intended to
correspond to the function of an underlying large-scale neural network. The
component production systems are highly interactive with each other, operate
in parallel, and have a task allocation regimen based on graded
specialization and resource availability.
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