With the growth of on-line information, the need for better resource location services is growing rapidly. A popular goal is to conduct search in terms of concepts, rather than wo...
Peter Clark, John Thompson, Heather Holmback, Lisb...
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
We present a novel approach to plan recognition in which graph construction and analysis is used as a paradigm. We use a graph structure called a Goal Graph for the plan recogniti...
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
Developing tools that allow non-programmers to enter knowledge has been an ongoing challenge for AI. In recent years researchers have investigated a variety ofpromising approaches...