1166 search results - page 93 / 234 » Negotiating Using Rewards |
ICRA
2009
IEEE
14 years 4 months ago
2009
IEEE
Abstract— Least-squares policy iteration is a useful reinforcement learning method in robotics due to its computational efficiency. However, it tends to be sensitive to outliers...
BMCV
2000
Springer
14 years 2 months ago
2000
Springer
Recent psychological and neurological evidence suggests that biological object recognition is a process of matching sensed images to stored iconic memories. This paper presents a p...
ICALT
2007
IEEE
13 years 12 months ago
2007
IEEE
Using adaptive, personalized courses is rewarding, as it can create a better learning experience, tailored for a specific learner’s needs. The process of creating these courses,...
AAMAS
2002
Springer
13 years 10 months ago
2002
Springer
In reinforcement learning, an agent tries to learn a policy, i.e., how to select an action in a given state of the environment, so that it maximizes the total amount of reward it ...
NIPS
2001
13 years 11 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...