Abstract. We suggest that the primary motivation for an agent to construct a symbol-meaning mapping is to solve a task. The meaning space of an agent should be derived from the tas...
Samarth Swarup, Kiran Lakkaraju, Sylvian R. Ray, L...
1 Example-based super-resolution recovers missing high frequencies in a magnified image by learning the correspondence between co-occurrence examples at two different resolution le...
We describe an extension of the virtual volume concept to multiple sensors. Data from multiple sensors are combined in real-time and mapped into a constantly updating three-dimens...
Managing semantic heterogeneity is a complex task. One solution involves matching like terms to each other. We view Match as an operator that takes two graph-like structures (e.g....
Pavel Shvaiko, Fausto Giunchiglia, Paulo Pinheiro ...
Abstract—Putative brain processes responsible for understanding language are based on spreading activation in semantic networks, providing enhanced representations that involve c...