170 search results - page 23 / 34 » Learning to play Tetris applying reinforcement learning meth... |
EXPERT
2008
14 years 9 months ago
2008
Natural language technologies have been long envisioned to play a crucial role in transitioning from the current Web to a more "semantic" Web. If anything, the significa...
73
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IJCNN
2006
IEEE
15 years 3 months ago
2006
IEEE
Abstract— Over the years, many improvements and refinements of the backpropagation learning algorithm have been reported. In this paper, a new adaptive penalty-based learning ex...
109
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CIG
2006
IEEE
15 years 3 months ago
2006
IEEE
Abstract— This paper compares the use of temporal difference learning (TDL) versus co-evolutionary learning (CEL) for acquiring position evaluation functions for the game of Othe...
ROBOCUP
2000
Springer
15 years 1 months ago
2000
Springer
Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...