MOSAIC: a macroconnectionist organization system for artificial intelligence computation

The authors present MOSAIC, an expert-system generator which uses a macroconnectionist approach to implement a dynamic system of knowledge representation. Each fragment of knowledge, termed a neuronic, integrates both declarative and procedural knowledge representation. The inference mechanism is fully distributed over the knowledge base, which eliminates the separation between knowledge and the treatment process. The macroconnectionist approach is derived from neurobiological models in which the basic unit corresponds to a system of neurons and not to a single neuron. This organization is positioned at an intermediate level between cognitive psychology and elementary neurobiology. However, the definition of a neuronic is recursive and makes it possible to integrate into the same system entities situated at different levels of complexity. MOSAIC uses both artificial-intelligence concepts (e.g., explicit inference strategies) and connectionist concepts (e.g., inference mechanisms based on the propagation of activation of dynamic contexts). A prototype based on these concepts has been constructed and its first medical application is being tested.<>