Can AI planners solve practical problems?
Computational Intelligence
STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
A model-based approach to blame assignment: revising the reasoning steps of problem solvers
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Perceptually grounded self-diagnosis and self-repair of domain knowledge
Knowledge-Based Systems
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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.