This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
We develop a method for detecting symmetries in arbitrary games and exploiting these symmetries when using tree search to play the game. Games in the General Game Playing domain a...
One of the most challenging issues in managing the large and diverse data available on the World Wide Web is the design of interactive systems to organize and represent information...
We present our efforts to create a large-scale, semi-automatically annotated parallel corpus of cleft constructions. The corpus is intended to reduce or make more effective the ma...
In this paper, we propose classifier ensemble selection for Named Entity Recognition (NER) as a single objective optimization problem. Thereafter, we develop a method based on gen...