Description: Modern cognitive architectures allow researchers to quickly build cognitive models that make use of established cognitive theory. The most prevalent of these is ACT-R, which combines a robust declarative memory system with a constrained production system for executive control and a detailed sensorimotor module that captures common human- computer interaction effects. This workshop will introduce the major components of ACT-R using hands-on examples of running models. We will be using the Python ACT-R syntax, which has been developed to make ACT- R more accessible to an audience without extensive programming experience.
Presented by: Terry Stewart – a postdoctoral fellow at the Centre for Theoretical Neuroscience at the University of Waterloo. His research has included models of game playing via learned sequential dependencies, group dynamics via internal predictions, and the repurposing of cognitive components. The common theme has been the use of mechanistic cognitive models capable of explaining a broad range of phenomena using consistent components that can be mapped on to particular brain areas. His current research involves developing a realistic neural implementation of the core of ACT-R, and exploring the behavioural and neural implications of such a model.
Where: University of Basel, Switzerland
When: 08/03/2009 – 08/04/2009