1235 search results - page 16 / 247 » Reinforcement learning in a nutshell |
NIPS
2004
13 years 9 months ago
2004
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
AAAI
2010
13 years 9 months ago
2010
IJCAI
2007
13 years 9 months ago
2007
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
JMLR
2012
11 years 10 months ago
2012
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
ICCBR
2009
Springer
14 years 2 months ago
2009
Springer
This work presents a new approach that allows the use of cases in a case base as heuristics to speed up Reinforcement Learning algorithms, combining Case Based Reasoning (CBR) and ...