We consider a resource selection game with incomplete information about the resource-cost functions. All the players know is the set of players, an upper bound on the possible cos...
In this paper we investigate the relation between transfer learning in reinforcement learning with function approximation and supervised learning with concept drift. We present a n...
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...