Integrating marker-passing and problem-solving: a spreading-activation approach to improved choice in planning
Semantic interpretation and the resolution of ambiguity
Semantic interpretation and the resolution of ambiguity
The berkeley UNIX consultant project
Computational Linguistics
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Memory and Context for Language Interpretation
Memory and Context for Language Interpretation
Concretion Inferences in NAtural Language Understanding
GWAI '87 Proceedings of the 11th German Workshop on Artificial Intelligence
A Unified Theory of Inference for Text Understanding
A Unified Theory of Inference for Text Understanding
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
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Potentially, the advantages of marker-passing over local connectionist techniques for associative inference are (1) the ability to differentiate variable bindings, and (2) reduction in the search space and/or number of processing elements. However, the latter advantage has mostly been realized at the expense of accuracy and predictability. In this paper we consider a class of associative inference to which marker passing is often applied, variously called abductive inference, schema selection, or pattern completion. Analysis of marker semantics in a standard semantic net representation leads to a proposal for more strictly regulated marker propagation. An implementation strategy employing an augmented relaxation network is outlined.