35 search results - page 2 / 7 » Balancing Multiple Sources of Reward in Reinforcement Learni... |
AGENTS
2001
Springer
13 years 9 months ago
2001
Springer
We report on the use of reinforcement learning with Cobot, a software agent residing in the wellknown online community LambdaMOO. Our initial work on Cobot (Isbell et al.2000) pro...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
GECCO
2006
Springer
13 years 9 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...
EUROCAST
2007
Springer
13 years 11 months ago
2007
Springer
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...