56 search results - page 4 / 12 » Q-Learning in Continuous State and Action Spaces |
AAMAS
2007
Springer
14 years 7 days ago
2007
Springer
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
ICFEM
2009
Springer
14 years 18 days ago
2009
Springer
An extension to action systems is presented facilitating the modeling of continuous behavior in the discrete domain. The original action system formalism has been developed by Back...
ICRA
2009
IEEE
14 years 21 days 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...
AUTOMATICA
2007
13 years 6 months ago
2007
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
UAI
2004
13 years 7 months ago
2004
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...