Many current state-of-the-art planners rely on forward heuristic search. The success of such search typically depends on heuristic distance-to-the-goal estimates derived from the ...
The association of perception and action is key to learning by observation in general, and to programlevel task imitation in particular. The question is how to structure this info...
Given sensors to detect object use, commonsense priors of object usage in activities can reduce the need for labeled data in learning activity models. It is often useful, however,...
Shiaokai Wang, William Pentney, Ana-Maria Popescu,...
Interaction between heterogeneous agents can raise some problems since agents may not use the same models and concepts. Therefore, the use of some mechanisms to achieve interoperab...
Laurent Vercouter, Sara J. Casare, Jaime Sim&atild...
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Computational cognitive modeling has recently emerged as one of the hottest issues in the AI area. Both symbolic approaches and connectionist approaches present their merits and d...
Many methods, including supervised and unsupervised algorithms, have been developed for extractive document summarization. Most supervised methods consider the summarization task ...
Motivated by basic ideas from formal concept analysis, we propose two ways to directly encode closure operators on finite sets in a 3-layered feed forward neural network.
Semantic systems for the representation of declarative knowledge are usually unconnected to neurobiological mechanisms in the brain. In this paper we report on efforts to bridge t...