The society of mind
The mathematics of inheritance systems
The mathematics of inheritance systems
Communications of the ACM
Computer
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Multilayer feedforward networks are universal approximators
Neural Networks
Recognition of semantically incorrect rules: a neural-network approach
IEA/AIE '90 Proceedings of the 3rd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 2
Foundations of cognitive science
Foundations of cognitive science
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Similarity and analogical reasoning
Similarity and analogical reasoning
Two-tiered concept meaning, inferential matching, and conceptual cohesiveness
Similarity and analogical reasoning
A connectionist model for commonsense reasoning incorporating rules and similarities
Knowledge Acquisition
Beyond associative memories: logics and variables in connectionist models
Information Sciences: an International Journal
Integrating Marker Passing and Problem Solving: A Spreading Activation Approach to Improved Choice in Planning
Symbolic Logic and Mechanical Theorem Proving
Symbolic Logic and Mechanical Theorem Proving
Inside Case-Based Reasoning
A Recency Inference Engine for Connectionist Knowledge Bases
Applied Intelligence
Integrating Linguistic Primitives in Learning Context-Dependent Representation
IEEE Transactions on Knowledge and Data Engineering
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In this paper, we propose a model for structuring knowledge in vague and continuous domains where similarity plays a role in coming up with plausible inferences. The model consists of two levels, one of which is an inference network with nodes representing concepts and links representing rules connecting concepts, and the other is a microfeature-based replica of the first level. Based on the interaction between the concept nodes and microfeature nodes in the model, inferences are facilitated and knowledge not explicitly encoded in a system can be deduced via mixed similarity matching and rule application. The model is able to take account of many important desiderata of plausible reasoning and produces sensible conclusions accordingly. Examples will be presented to illustrate the utility of the model in structuring knowledge to enable useful inferences to be carried out in several domains.