Artificial intelligence publications

We have implemented an approach in which rapid improvement in performance at suggesting reusable text is achieved by learning from limited user feedback.

As a near-term goal, we are focusing on enabling subject matter experts (SMEs) to construct declarative knowledge bases (KBs) from 50 pages of a science textbook in the domains of…

We first show that for an STN, these messages can be represented compactly as sub-STNs. We then present an efficient message passing scheme for computing the minimal constraints of an…

We develop a preference model designed to capture user scheduling preferences for overconstrained meeting requests between multiple people, and a methodology for preference elicitation to initially populate this model.

We describe an intelligent personal assistant that has been developed to aid a busy knowledge worker in managing time commitments and performing tasks. The system draws on a diverse set…

Our model for proactive assistance employs a meta-level layer to identify potentially helpful actions and determine when it is appropriate to perform them. We conclude by identifying technical challenges in…

We describe a deduction-based approach to biocomputation that semiautomatically combines knowledge, software, and data to satisfy goals expressed in a high-level biological language.

This position paper outlines some initial thoughts on desired forms of proactive behavior, and identifies technical challenges in developing systems that embody such behaviors.

We present a system for extracting useful information from multi-party meetings and presenting the results to users via a browser.

We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in contrast with comparable generative models,…