Artificial Intelligence

The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

We develop a semantics-driven, automated approach for dynamically performing rigorous scientific studies.

Explainability has been a goal for Artificial Intelligence (AI) systems since their conception, with the need for explainability growing as more complex AI models are increasingly used in critical, high-stakes settings such as healthcare.

Machine learning allows computers to learn a model for a given task, such as face recognition, with a high degree of accuracy, using data. However, after these models are generated, they are often treated as black boxes by developers and the limitations of a model are often unknown to end-users.

In plan reuse, refitting is the process of modifying an existing plan to make it applicable to a new problem situation. An efficient refitting strategy needs to be conservative, i.e., it should minimally modify the existing plan to fit it to the new problem situation.

Description logic-based configuration applications have been used within AT&T since 1990 to process over two and a half billion dollars worth of orders.

This paper compares three commitment strategies for HTN planning: (1) a strategy that delays variable bindings as much as possible; (2) a strategy in which no non-primitive task is expanded until all variable constraints are committed; and (3) a strategy that chooses between expansion and variabl

This paper describes an environment for supporting very large ontologies. The system can be used on single PCs, workstations, a cluster of workstations, and high-end parallel supercomputers.

In this paper we explain how we applied genetic programming to behavior-based team coordination in the RoboCup Soccer Server domain. Genetic programming is a promising new method for automatically generating functions and algorithms through natural selection.

One difficulty with existing theoretical work on HTN planning is that it does not address some of the planning constructs that are commonly used in HTN planners for practical applications.

One of the unique advantages brought by the Semantic Web is that semantic web languages, such as RDF and OWL, offer a small but expressive set of common ontological constructs for agents to share knowledge on the Web.