162 search results - page 21 / 33 » Off-Policy Temporal Difference Learning with Function Approx... |
139
Voted
ICMLA
2010
15 years 10 days ago
2010
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
113
Voted
IJCNN
2006
IEEE
15 years 8 months ago
2006
IEEE
— This paper shows the advantage of using neural network modularity over conventional learning schemes to approximate complex functions. Indeed, it is difficult for artificial ...
111
Voted
ESANN
2003
15 years 3 months ago
2003
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
130
click to vote
ICML
2008
IEEE
16 years 3 months ago
2008
IEEE
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
79
Voted
ICPR
2006
IEEE
16 years 3 months ago
2006
IEEE
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...