69 search results - page 6 / 14 » Dynamic Scheduling in Petroleum Process using Reinforcement ... |
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...
ECAL
2001
Springer
13 years 12 months ago
2001
Springer
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
AIIA
2007
Springer
14 years 1 months ago
2007
Springer
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
PKDD
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
ISNN
2007
Springer
14 years 1 months ago
2007
Springer
A novel online dynamic value system for machine learning is proposed in this paper. The proposed system has a dual network structure: data processing network (DPN) and information ...