147 search results - page 2 / 30 » Policy Gradient in Continuous Time |
ICML
2003
IEEE
14 years 10 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...
AIPS
2007
13 years 12 months ago
2007
We present an any-time concurrent probabilistic temporal planner that includes continuous and discrete uncertainties and metric functions. Our approach is a direct policy search t...
AAAI
2010
13 years 11 months ago
2010
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
NIPS
2008
13 years 11 months ago
2008
Our setting is a Partially Observable Markov Decision Process with continuous state, observation and action spaces. Decisions are based on a Particle Filter for estimating the bel...
ECML
2007
Springer
14 years 3 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...