Model-Based Reasoning and Diagnosis
A central issue in knowledge representation is to effectively describe
the ways in which complex systems behave, so that software agents can use
these descriptions for flexible problem solving without a programmer
spending time to explicitly code sequences of problem-specific decisions.
Model-Based Reasoning is based on the idea of a knowledge base (the "model')
that describes a particular problem area in terms of the behaviour of its
smaller building blocks (e.g., pumps and valves in hydraulic systems,
switches in electrical systems, or gates in digital circuits). A general
problem-solving engine then experiments with different ways in which these
components can interact to find solutions to problems such as "why doesn't
this device work?" (diagnosis) or "how can I put these parts together to get
a functioning system" (configuration and design).
Research in model-based diagnosis searches for
representations and algorithms for identifying faults in technical devices
ranging from car engines to space probes. Once designed, a diagnosis tool
can use a given model for multiple systems from that problem domain,
identify complex fault combinations, distinguish between different kinds of
faults, make repair suggestions, and generate fault trees for training and
documentation purposes, using a set of domain independent reasoning
mechanisms.