The Role of Cognitive Architecture in Modeling the User
Soar's Learning Mechanism
Bibliographic Data
| ID | 15216280 |
|---|---|
| Authors | Andrew Howes (0000-0003-4251-1127, Cardiff University, corresponding author), Richard M Young (0000-0003-2289-6496, University of Hertfordshire) |
| Year | 1997 |
| Volume | 12 |
| Issue | 4 |
| Pages | 311-343 |
| Publication date | 1997-12-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Human-Computer Interaction (JOURNAL) |
| Journal identifiers | ISSN: 0737-0024 • E-ISSN: 1532-7051 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1207/s15327051hci1204_2 |
| OpenAlex | W2030860531 |
| Language | EN |
| Citations received | 2 |
| References cited | 37 |
What is the role of a cognitive architecture in shaping a model built within it? Compared with a model 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 ruled out. We illustrate a variety 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 in 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 modeling, 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 behavior depends on the compliancy of the model
Cognition · Cognitive architecture · Cognitive model · Cognitive science · Human–computer interaction · Machine learning · Mechanism (biology · Programming language · Set (abstract data type · Soar · Variety (cybernetics · Computer Science · Human-Automation Interaction and Safety · Intelligent Tutoring Systems and Adaptive Learning · Personal Information Management and User Behavior · Psychology · Architecture · Artificial Intelligence
| Citations per year | 0.07 |
|---|---|
| Citation span | 1997 - 2007 (11) |
| Highly cited | No |