51 search results - page 1 / 11 » Characterizing reinforcement learning methods through parame... |
ML
2011
ACM
12 years 7 months ago
2011
ACM
AI
2006
Springer
13 years 8 months ago
2006
Springer
In the context of probabilistic verification, we provide a new notion of trace-equivalence divergence between pairs of Labelled Markov processes. This divergence corresponds to the...
IJCNN
2006
IEEE
13 years 10 months ago
2006
IEEE
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
NIPS
2007
13 years 5 months ago
2007
Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...