Author: Karen Myers

Universal attachment is a domain-independent mechanism for integrating diverse representation and reasoning methods into hybrid frameworks that contain a subsystem based on deduction over logical formulas.

Agents situated in dynamic and unpredictable environments require several capabilities, including synthesizing and executing plans while continuing to be responsive to the world.

The fundamental ideas behind FASTUS are retained in the current system: an architecture consisting of cascaded finite state transducers, each providing an additional level of analysis of the input, together with merging of the final results.

We describe an architecture of mobile robots based on the the concept of semi-autonomy that employs communication with a human advisor in order to simplify the tasks of map construction and navigation.

The framework consists of a set of generic operations on analogical structures and accompanying inference methods for integrating analogical and sentential information.

In this paper, we describe a compilation-based method for automatically generating new programs and new universal attachments to those programs given a base set of existing programs and universal attachments.

In this paper, we illustrate how such inferences add a new dimension of complexity to reasoning about change and show that failure to allow for such inferences can result in an unwarranted loss of derived information.