Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Methods that learn from prior information about input features such as generalized expectation (GE) have been used to train accurate models with very little effort. In this paper,...
CONDORCKD is a system implementing a novel approach to discovering knowledge from data. It addresses the issue of relevance of the learned rules by algebraic means and explicitly ...
Jens Fisseler, Gabriele Kern-Isberner, Christoph B...
In this paper we study the use of experts algorithms in a multiagent setting. In this paper we allow agents to use multiple experts and explore different experts algorithms that a...