Although engineering models of user behavior have enjoyed a rich history in HCI, they have yet to have a widespread impact due to the complexities of the modeling process. In this paper we describe a development system in which designers generate predictive cognitive models of user behavior simply by demonstrating tasks on HTML mock-ups of new interfaces. Keystroke-Level Models are produced automatically using new rules for placing mental operators, then implemented in the ACT-R cognitive architecture. They interact with the mock-up through integrated perceptual and motor modules, generating behavior that is automatically quantified and easily examined. Using a query-entry user interface as an example [19], we demonstrate that this new system enables more rapid development of predictive models, with more accurate results, than previously published models of these tasks.

Describes a multi-layered hierarchical motion planning strategy for a class of self-reconfigurable modular robotic systems, I-Cubes. The approach is based on the synthesis of motion on the basis of metacubes, which have a particular structure possessing 8 Cubes and 16 Links. The developed strategy organizes the metacube motions and the corresponding cube-level motions. At the lowest level, link motions are generated. The resulting system is demonstrated to be capable of performing a pre-specified task of moving from one position/shape to another. The paper describes the latest results of our planning strategy through some experimentally justified examples.