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IROS
2008
IEEE
125views Robotics» more  IROS 2008»
16 years 1 months ago
Dynamic correlation matrix based multi-Q learning for a multi-robot system
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Hongliang Guo, Yan Meng
AIEDAM
1998
87views more  AIEDAM 1998»
15 years 6 months ago
Learning to set up numerical optimizations of engineering designs
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
Mark Schwabacher, Thomas Ellman, Haym Hirsh
AIMSA
2008
Springer
16 years 28 days ago
Prototypes Based Relational Learning
Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. However, they do not scale up well, specially in domains where there is a time bound for c...
Rocío García-Durán, Fernando ...
TCS
2010
15 years 5 months ago
Active learning in heteroscedastic noise
We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
András Antos, Varun Grover, Csaba Szepesv&a...
HPDC
2009
IEEE
15 years 10 months ago
Maestro: a self-organizing peer-to-peer dataflow framework using reinforcement learning
In this paper we describe Maestro, a dataflow computation framework for Ibis, our Java-based grid middleware. The novelty of Maestro is that it is a self-organizing peer-to-peer s...
C. van Reeuwijk