170 search results - page 17 / 34 » Heuristic Selection of Actions in Multiagent Reinforcement L... |
NN
2002
Springer
13 years 7 months ago
2002
Springer
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
FLAIRS
2008
13 years 9 months ago
2008
Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
AAAI
1998
13 years 8 months ago
1998
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
IWANN
1999
Springer
13 years 11 months ago
1999
Springer
To avoid the curse of dimensionality, function approximators are used in reinforcement learning to learn value functions for individual states. In order to make better use of comp...
CORR
2011
Springer
12 years 11 months ago
2011
Springer
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...