Time is a crucial variable in planning and often requires special attention since it introduces a specific structure along with additional complexity, especially in the case of dec...
In this theoretical contribution we provide mathematical proof that two of the most important classes of network learning - correlation-based differential Hebbian learning and rew...
Christoph Kolodziejski, Bernd Porr, Minija Tamosiu...
Massively multiplayer online computer games are played in complex, persistent virtual worlds. Over time, the landscape of these worlds evolves and changes as players create and pe...
This paper presents a method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal, and discusses several issues in applying the reinforcement...
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...