160 search results - page 6 / 32 » Optimization on a Budget: A Reinforcement Learning Approach |
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
UAI
2001
13 years 9 months ago
2001
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
ICAI
2004
13 years 9 months ago
2004
An explicit exploration strategy is necessary in reinforcement learning (RL) to balance the need to reduce the uncertainty associated with the expected outcome of an action and the...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
ICMLA
2010
13 years 5 months ago
2010
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...