Richard M Young: Recent papers

The papers below have recently been published, or are in press. Comments are welcome.

You can contact me by email as R.M.Young@herts.ac.uk.


Embodied models as simulated users: Introduction to this Special Issue on Applying Cognitive Models to Interface Design

Frank E Ritter (Penn State University)
Richard M Young (University of Hertfordshire)

International Journal of Human-Computer Studies(2001), in press.

ABSTRACT

Cognitive models provide a means for applying what is known about psychology to the design of interfaces, thereby improving their quality and usability. Existing uses of models include predicting time and errors for users to perform tasks, acting as embedded assistants to help users perform their tasks, and serving as surrogate users. Treating the design of human-computer interfaces as a form of engineering design requires the development and application of user models. A recent trend is for models to be built within the fixed framework of a cognitive architecture, which has been extended by the addition of simulated eyes and hands, enabling the construction of embodied models. Being embodied allows models to interact directly with interfaces. The resulting models can be used to evaluate the interfaces they use, and serve as explanations of users' behavior. The papers in this Special Issue point to a new route for the future, one in which models built within embodied cognitive architectures provide information for the design of better interfaces.

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Production Systems in Cognitive Psychology

Richard M Young (University of Hertfordshire)

In N. J. Smelser & P. B. Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences. Pergamon, in press.

ABSTRACT

A production system consists of a collection of if-then rules that together form an information-processing, computer simulation model of some cognitive task, or range of tasks. A production system operates by means of a recognise-act cycle, in which the rule whose condition part is satisfied is identified, and its actions taken. Production systems have special properties that make them highly suited to modelling cognition, including their combination of parallel and serial processing, the independence of their rules, and their flexible control. From their origins as models of problem solving, production systems have grown to become a major formalism for modelling cognitive skill and aspects of learning, in areas such written arithmetic, reading, and knowledge-intensive areas of expertise such as chess playing and medical diagnosis. Production systems lend themselves well to the modelling of learning and cognitive development. Since the 1990s, they have become increasingly identified with the topic of integrated cognitive architectures.

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Supporting Cognitive Models as Users

Frank E Ritter (Penn State University)
Gordon D Baxter (University of Nottingham)
Gary Jones (University of Nottingham)
Richard M Young (University of Hertfordshire)

ACM Transactions on Computer-Human Interaction(June 2000), 7(2), 141-173.

ABSTRACT

Cognitive models are computer programs that simulate human performance of cognitive skills. They have been useful to HCI by predicting task times, by assisting users, and by acting as surrogate users. If cognitive models could interact with the same interfaces that users do, the models would be easier to develop and would be easier to apply as interface testers. This approach can be encapsulated as a cognitive model interface management system (CMIMS), which is analogous to and based on a user interface management system (UIMS). We present five case studies using three different UIMSes. These show how models can interact with interfaces using an interaction mechanism that is designed to apply to all interfaces generated within a UIMS. These interaction mechanisms start to support and constrain performance in the same ways that human performance is supported and constrained by interaction. Most existing UIMSes can and should be extended to create CMIMSes, and models can and should use CMIMSes to look at larger and more complex tasks. CMIMSes will help to further exploit the synergy between the disciplines of cognitive modeling and HCI by supporting cognitive models as users.

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The Soar Cognitive Architecture and Human Working Memory

Richard M Young (University of Hertfordshire)
& Richard L Lewis (The Ohio State University)

Chapter 7 of: A. Miyake & P. Shah (eds), Models of Working Memory: Mechanisms of Active Maintenance and Executive Control, 224-256. Cambridge University Press, 1999.

ABSTRACT

From the viewpoint of the Soar cognitive architecture, the term "working memory" (WM) refers to the psychological mechanisms that maintain information retrieved or created during the performance of a task. The following are the five key points made in the chapter concerning Soar's treatment of human WM:
(1) Soar is not specifically a "model of WM", but rather a cognitive architecture of broad scope, which focuses on the functional capabilities needed for a memory system to support performance in a range of cognitive tasks. The functions of working memory are distributed across multiple components of the architecture, including the long-term production memory.
(2) Even in a cognitive architecture with an unbounded dynamic memory, WM limitations can arise on functional grounds. Where such functional accounts exist, they take theoretical priority over capacity-based explanations of WM phenomena.
(3) Soar does not currently include any capacity limits on its dynamic memory (SDM), but is compatible with certain such limitations. In particular, a constraint that SDM can hold at most two items of the same "type" (suitably defined) yields a coherent explanation for many psycholinguistic phenomena in the comprehension of sentences. This constraint is motivated by computational efficiency concerns, and embodies the general principle of similarity-based interference (Baddeley & Logie; Cowan; Schneider; and O'Reilly, Braver & Cohen -- all in this volume).
(4) Soar emphasises the role of learning in WM phenomena, even on tasks which experimentally are regarded as concerning just "performance". The moral is that WM cannot coherently be studied independently of long-term memory and while ignoring learning.
(5) Soar stresses the recognitional usage of information in long-term memory acquired as a by-product of earlier task performance. It therefore has close links to other approaches which emphasise the involvement of long-term memory in WM, and may be able to offer a computational process model for "long-term WM" (Ericsson & Delaney, this volume).

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The Role of Cognitive Architecture in Modelling the User: Soar's Learning Mechanism

Andrew Howes (Cardiff University of Wales)
& Richard M Young (Psychology Department, University of Hertfordshire)

Human-Computer Interaction(1997), 12, 311-343.

ABSTRACT

What is the role of a cognitive architecture in shaping a model built within it? Compared with a model just written in a programming language, the cognitive architecture offers theoretical constraints. These constraints can be "soft", in that some ways of constructing a model are facilitated and others made more difficult, or they can be "hard", in that certain aspects of a model are enforced and others are ruled out. We illustrate various of these possibilities. In the case of Soar, its learning mechanism is sufficiently constraining that it imposes hard constraints on models constructed within it. We describe how one of these hard constraints deriving from Soar's learning mechanism ensures that models constructed within Soar must learn a display-based skill and, other things being equal, must find display-based devices easier to learn than keyboard-based devices. We discuss the relation between architecture and model is terms of the degree to which a model is "compliant" with the constraints set by the architecture. Although doubts are sometimes expressed as to whether cognitive architectures have any empirical consequences for user modelling, our analysis shows that they do. Architectures play their part by imposing theoretical constraints on the models constructed within them, and the extent to which the influence of the architecture shows through in the model's behaviour depends on the compliancy of the model.

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Rational Analysis of Exploratory Choice

Richard M Young (Psychology Department, University of Hertfordshire)

In M. Oaksford & N. Chater (Eds), Rational Models of Cognition,469-500. Oxford University Press, 1998.

ABSTRACT

This chapter extends Anderson's (1990) rational analysis of problem solving to a class of exploratory search situations that involve selecting one of a number of possible options, where little is known about the options before exploration begins. We formulate the situation as one of single-move, multi-stage search, where the probabilities of success of the different options are initially unknown, but where a range of assessment methods is available to provide information about each option. The assessment methods differ in their costs and in the quality of the information they deliver. The analysis defines an optimal strategy, which is applied to an experimentally studied task where a subject has to use an unfamiliar computer package. Simulation of the optimal strategy shows that it exhibits a number of features characteristic of the empirical data, such as repeated scanning of the menus, progressive focussing on a subset of the options, and iterative deepening of attention.

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A Microtheory of Visually-Derived Information

Richard M Young (Psychology Department, University of Hertfordshire)

Unpublished paper presented at meeting on Formal Aspects of Human-Computer Interaction (FAHCI-98), Sheffield, UK, 1998.

ABSTRACT

In human-computer interaction, information is most commonly conveyed from computer to user by being shown on a VDU or other kind of visual display. By seeing and interpreting what is shown on the display, users come to know things both about the objects on the display and about other entities those objects depict. From a formal point of view, how does this process "work"? This paper presents a simple microtheory of how users acquire information from visual displays. The intention is for the microtheory to serve as a standard analysis of visually-derived information, to be included as part of more complete formal descriptions of devices and users.

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A Dual-Space Model of Iteratively Deepening Exploratory Learning

John Rieman, Richard M Young (MRC Applied Psychology Unit, Cambridge, England) & Andrew Howes (School of Psychology, University of Cardiff, Wales)

International Journal of Human-Computer Studies(1996), 44, 743-775.

ABSTRACT

When users of interactive computers must work with new software without formal training, they rely on strategies for "exploratory learning". These include trial and error, asking for help from other users, and looking for information in printed and on-line documentation. This paper describes a cognitive model of exploratory learning, which covers both trial-and-error and instruction-taking activities. The model, implemented in Soar, is grounded in empirical data of subjects in a task-oriented, trial-and-error exploratory learning situation. A key empirical finding reflected in the model is the repeated scanning of a subset of the available menu items, with increased attention to items on each successive scan. This is explained in terms of dual search spaces, the external interface and the user's internal knowledge, both of which must be tentatively explored with attention to changing costs and benefits. The model implements this dual-space search by alternating between external scanning and internal comprehension, a strategy that gradually shifts its focus to a potentially productive route through an interface. Ways in which interfaces might be designed to capitalize on this behavior are suggested. The research demonstrates how cognitive modelling can describe behavior of the kind discussed by theories of "situated cognition".

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Learning Consistent, Interactive, and Meaningful Task-Action Mappings: A Computational Model

Andrew Howes (School of Psychology, University of Cardiff, Wales)
& Richard M Young (MRC Applied Psychology Unit, Cambridge, England)

Cognitive Science(1996), 20, 301-356.

ABSTRACT

Within the field of Human-Computer Interaction, the study of the interaction between people and computers has revealed many phenomena. For example, highly interactive devices, such as the Apple Macintosh, are often easier to learn and use than keyboard-based devices such as Unix. Similarly, consistent interfaces are easier to learn and use than inconsistent ones. This paper describes an integrated cognitive model designed to exhibit a range of these phenomena whilst learning task-action mappings: Action sequences for achieving simple goals such as opening a file in a wordprocessor. The model, called TAL, is of a user who is familiar with the basic operations of a keyboard and mouse, but unfamiliar with the particular menu structures, words, and actions required to use the device. The model is constructed in Soar and employs a single set of architectural mechanisms. It exhibits behaviour that captures human preference for consistent, interactive, and meaningful task-action mappings.

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