We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
The necessity for improved players and opponents in firstperson entertainment-based real-time artificial environments has inspired our research into artificial game players. We em...
We propose a framework for policy generation in continuoustime stochastic domains with concurrent actions and events of uncertain duration. We make no assumptions regarding the co...
Shoreline mapping and shoreline change detection are critical in many coastal zone applications. This paper presents results of the semi-automatic mapping of a coastal area of Lak...
We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...