50 search results - page 7 / 10 » Reinforcement Learning for Penalty Avoidance in Continuous S... |
ICRA
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
NIPS
1996
13 years 8 months ago
1996
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
KES
1998
Springer
13 years 11 months ago
1998
Springer
An agent must acquire internal representation appropriate for its task, environment, sensors. As a learning algorithm, reinforcement learning is often utilized to acquire the rela...
ICANNGA
2007
Springer
14 years 1 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...