458 search results - page 66 / 92 » Q-Decomposition for Reinforcement Learning Agents |
ACL
1998
13 years 9 months ago
1998
This paper describes a novel method by which a dialogue agent can learn to choose an optimal dialogue strategy. While it is widely agreed that dialogue strategies should be formul...
AAAI
2010
13 years 9 months ago
2010
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
AGI
2011
12 years 11 months ago
2011
Under Legg’s and Hutter’s formal measure [1], performance in easy environments counts more toward an agent’s intelligence than does performance in difficult environments. An ...
AGI
2008
13 years 9 months ago
2008
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...