A set of experiments for learning the values of chess pieces is described for the popular chess variants Crazyhouse Chess, Suicide Chess, and Atomic Chess. We follow an establishe...
This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal ...
We present a novel method to control a biped humanoid robot to walk on unknown inclined terrains, using an online learning algorithm to estimate in real-time the local terrain fro...
The generalization of policies in reinforcement learning is a main issue, both from the theoretical model point of view and for their applicability. However, generalizing from a se...