This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
The stream processing characteristics of many embedded system applications in multimedia and networking domains have led to the advent of stream based programming formats. Several ...
We discuss multiclass-multilabel classification problems in which the set of classes is extremely large. Most existing multiclass-multilabel learning algorithms expect to observe ...
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
A large number of network applications today allow several users to interact together using the many-to-many service mode. In many-to-many communication, also referred to as group ...