133 search results - page 3 / 27 » Hierarchical Policy Gradient Algorithms |
AAAI
2011
12 years 5 months ago
2011
In environmental and natural resource planning domains actions are taken at a large number of locations over multiple time periods. These problems have enormous state and action s...
IJCAI
2001
13 years 6 months ago
2001
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
ECML
2007
Springer
13 years 11 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 ...
NN
2010
Springer
13 years 3 months ago
2010
Springer
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...