The objective of the Maximal Constraint Satisfaction Problem (Max-CSP) is to find an instantiation which minimizes the number of constraint violations in a constraint network. In t...
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
Abstract. Searching objects within a catalog is a problem of increasing importance, as the general public has access to increasing volumes of data. Constraint programming has addre...
Context-aware applications rely on the ability to perceive the state of the surrounding environment. In this paper, we address a class of such applications where real-time guarant...