The concept of diversity was successfully introduced for recommender-systems. By displaying results that are not only similar to a target problem but also diverse among themselves,...
In this paper we present an approach for reducing the memory footprint requirement of temporal difference methods in which the set of states is finite. We use case-based generaliza...
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
The vast majority of research on AI planning has focused on automated plan recognition, in which a planning agent is provided with a set of inputs that include an initial goal (or ...