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» On learning in agent-centered search
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ICAI
2004
15 years 1 months ago
Action Inhibition
An explicit exploration strategy is necessary in reinforcement learning (RL) to balance the need to reduce the uncertainty associated with the expected outcome of an action and the...
Myriam Abramson
AIPS
2010
15 years 2 days ago
Iterative Learning of Weighted Rule Sets for Greedy Search
Greedy search is commonly used in an attempt to generate solutions quickly at the expense of completeness and optimality. In this work, we consider learning sets of weighted actio...
Yuehua Xu, Alan Fern, Sung Wook Yoon
ICML
2002
IEEE
16 years 20 days ago
Pruning Improves Heuristic Search for Cost-Sensitive Learning
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Valentina Bayer Zubek, Thomas G. Dietterich
SIGIR
2011
ACM
14 years 2 months ago
Parallel learning to rank for information retrieval
Learning to rank represents a category of effective ranking methods for information retrieval. While the primary concern of existing research has been accuracy, learning efficien...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
ICML
2009
IEEE
16 years 20 days ago
Binary action search for learning continuous-action control policies
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Jason Pazis, Michail G. Lagoudakis