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Past Projects

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AURA

Automated User-Centered Reasoning and Acquisition System

The goal of this project is to build a generic knowledge acquisition capability for Physics, Chemistry, and Biology. Using the system, the scientists will be able to formulate their knowledge in the three science domains, and the high school students will be able to pose Advanced-Placement style questions and get user appropriate explanations.

Rationale Capture

Automated Capture of Design Rationale

This project developed nondisruptive techniques for automatically acquiring rationale information for the detailed design process. The project produced a Rationale Construction Framework (RCF) system that monitors designer interactions with a CAD tool to produce a rich process history. This history is then structured and interpreted relative to a background theory of `design metaphors', thus enabling summarization and explanation of key elements of the design process.

Halo Pilot

A System for Representing Textbook Knowledge

The goal of the project is to demonstrate the current state-of-the-art in knowledge representation by attempting to answer the questions in an advance placement test in chemistry.

Shakey VI

Artificial Intelligence - Research and Applications

A 6th continuation of the umbrella project for AI research that used Shakey as a platform to drive the research.

Shakey V

Artificial Intelligence – Research and Applications

The fifth project using Shakey as a platform to test/demonstrate AI problems and approaches.

Aquaint

Aquaint: From Question-Answering to Information Seeking Dialogs

From question-answering to information-seeking dialogs.

Shakey

Application of Intelligent Automata to Reconnaissance

Development of the original robot Shakey for exploring AI problems.

SHAKEN

A Knowledge Entry System for Subject Matter Experts

The goal of SHAKEN project is to enable subject matter experts , without any assistance from AI technologists, to assemble the models of processes and mechanisms so that questions about them can be answered by declarative inference and simulation.

Advisable Planners

Advisable Planners

The Advisable Planners project sought to make AI planning technology more accessible and controllable through the metaphor of advisability. User-provided advice specifies characteristics for both the desired solution and the problem-solving process to be employed during plan generation. Such advice is specified in a high-level language that is natural and intuitive for users, then operationalized into constraints that direct the underlying planning technology.

This website does not contain information on all of our past or present projects.
For further information please contact us.

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