We present a powerful meta-clustering technique called Iterative Double Clustering (IDC). The IDC method is a natural extension of the recent Double Clustering (DC) method of Slon...
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
Zhe Li, Sven Wachsmuth, Jannik Fritsch, Gerhard Sa...
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
In this paper, we design a novel MRF framework which is called Non-Local Range Markov Random Field (NLRMRF). The local spatial range of clique in traditional MRF is extended to th...
This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...