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AAAI
2007
13 years 9 months ago
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
IPPS
1996
IEEE
13 years 11 months ago
Practical Parallel Algorithms for Dynamic Data Redistribution, Median Finding, and Selection
A common statistical problem is that of nding the median element in a set of data. This paper presents a fastand portable parallel algorithm for nding the median given a set of el...
David A. Bader, Joseph JáJá
EDBT
2009
ACM
136views Database» more  EDBT 2009»
14 years 2 months ago
Finding frequent co-occurring terms in relational keyword search
Given a set Q of keywords, conventional keyword search (KS) returns a set of tuples, each of which (i) is obtained from a single relation, or by joining multiple relations, and (i...
Yufei Tao, Jeffrey Xu Yu
ICML
2007
IEEE
14 years 8 months ago
Automatic shaping and decomposition of reward functions
This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
Bhaskara Marthi
AUSAI
2005
Springer
14 years 1 months ago
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning
: In order to scale to problems with large or continuous state-spaces, reinforcement learning algorithms need to be combined with function approximation techniques. The majority of...
Peter Vamplew, Robert Ollington