In this paper, we propose a general two-dimensional hidden Markov model (2D-HMM), where dependency of the state transition probability on any state is allowed as long as causality...
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
We propose a comprehensive solution to handle memory-overflow problems in multitasking embedded systems thereby improving their reliability and availability. In particular, we pro...
E-commerce has transformed the way firms develop their pricing strategies, producing shift away from fixed pricing to dynamic pricing. In this paper, we use two different Estim...
Siddhartha Shakya, Fernando Oliveira, Gilbert Owus...
Abstract. Many reinforcement learning domains are highly relational. While traditional temporal-difference methods can be applied to these domains, they are limited in their capaci...
Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richa...