SOAR: an architecture for general intelligence
Artificial Intelligence
Context-based representation of intelligent behavior in training simulations
Transactions of the Society for Computer Simulation International
Autonomous Automobile Behavior through Context-Based Reasoning
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference
Representation of procedures and practices in contextual graphs
The Knowledge Engineering Review
Evolving models from observed human performance
Evolving models from observed human performance
ACT-R: a theory of higher level cognition and its relation to visual attention
Human-Computer Interaction
Understanding context before using it
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Task-Realization models in contextual graphs
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
| Hi-index | 0.00 |
This paper describes an investigation that compared and contrasted Context-based Reasoning (CxBR) and Contextual Graphs (CxG), two paradigms used to represent human intelligence. The specific objectives were to increase understanding of both paradigms, identifying which, if either, excels at a particular function, and to look for potential synergism amongst them. We study these paradigms through ten different aspects, with some indication of which one excels at this particular facet of performance. We point out how they are complementary and finishes with a recommendation for a new synergistic approach, followed by an example of an application of the new approach to tactical