Daniel G. Shapiro

TL;DR: This article, which introduces a special issue on AmI, views the area from an artificial intelligence perspective.

TL;DR: Initial experiments indicate that a RUBRIC rule set better matches human retrieval judgment than a standard Boolean keyword expression, given equal amounts of effort in defining each.

TL;DR: The results indicate that some calculi appear to prevent the development of good queries while those whose behaviour is appropriately smooth can give satisfactory performance and the evidence suggests that as queries become more complex the impact of the choice of calculus is reduced.

TL;DR: This paper examines approaches to representing and utilizing hierarchical skills within the context of a cognitive architecture, and presents an alternative that has been developed within Icarus, another candidate architecture.

TL;DR: ICARUS is described, an integrated architecture for intelligent physical agents that supports long-term memories for hierarchical concepts and skills, along with mechanisms for recognizing concepts that hold in the environment, determining which skills are applicable, and selecting for execution the skill with the highest expected value.