Learning about Constraints by Reflection

A system's constraints characterizes what that system can do. However, a dynamic environment may require that a system alter its constraints. If feedback about a specific situation is available, a system may be able to adapt by reflecting on its own reasoning processes. Such reflection may be guided not only by explicit representation of the system's constraints but also by explicit representation of the functional role that those constraints play in the reasoning process. We present an operational computer program, Sirrine2 which uses functional models of a system to reason about traits such as system constraints. We further describe an experiment with Sirrine2 in the domain of meeting scheduling.

• Type: Conference
• Year: 2001
• Where: AI
• Authors: J. William Murdock, Ashok K. Goel
• Keywords: AI 2001, Artificial Intelligence, Explicit Representation, System's Constraints, System's Constraints Characterizes