575 search results - page 36 / 115 » Reinforcement Learning State Estimator |
NIPS
1996
14 years 11 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...
124
click to vote
AI
1998
Springer
14 years 9 months ago
1998
Springer
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
130
click to vote
WAPCV
2007
Springer
15 years 4 months ago
2007
Springer
The innovation of this work is the provision of a system that learns visual encodings of attention patterns and that enables sequential attention for object detection in real world...
AAAI
2008
15 years 6 days ago
2008
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
ECML
2007
Springer
15 years 4 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 ...