Artificial intelligence publications

We describe an AI-enhanced task management tool developed for a military environment, which differs from office environments in important ways: differing time scales, a focus on teams collaborating on tasks…

We present an action theory with the power to represent recursive plans and the capability to reason about and synthesize recursive workflow control structures.

We show that box invariance can be checked in cubic time for linear and affine systems, and that it remains decidable for classes of nonlinear systems of interest (with polynomial…

We show that simple efficient many-class learning can perform well for action prediction, significantly improving over previously published results and baselines.

A mixed-initiative agent for personal time management interacts not only with its human owner but also with other agents and humans that share or depend on the same time commitments.

In this paper, we argue that in dealing with ADLs, it is beneficial to exploit both their typical duration patterns and inherent hierarchical structures.

Inspired by popular co-training and domain adaptation methods, we propose a co-adaptation algorithm. The goal is improving the performance of a dialog act segmentation model by exploiting the vast amount…

We present an integrated task learning system (ITL) that learns executable procedures based on user demonstration and instruction, constituting a first step toward a broader solution for procedure management.

When creating algorithms or systems that are supposed to be used by people, we should be able to adopt a “binocular” view of users’ interaction with intelligent systems: a view…

This paper presents a case study that explores how to instantiate a question asking framework to select questions for a particular type of learner used within learning by demonstration systems,…