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ECML
2003
Springer
14 years 2 months ago
Self-evaluated Learning Agent in Multiple State Games
Abstract. Most of multi-agent reinforcement learning algorithms aim to converge to a Nash equilibrium, but a Nash equilibrium does not necessarily mean a desirable result. On the o...
Koichi Moriyama, Masayuki Numao
ICML
2005
IEEE
14 years 9 months ago
Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
IJON
2007
120views more  IJON 2007»
13 years 9 months ago
Comparison of dynamical states of random networks with human EEG
Existing models of EEG have mainly focused on relations to network dynamics characterized by firing rates [L. de Arcangelis, H.J. Herrmann, C. Perrone-Capano, Activity-dependent ...
Ralph Meier, Arvind Kumar, Andreas Schulze-Bonhage...
AAAI
2012
11 years 11 months ago
Relative Attributes for Enhanced Human-Machine Communication
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
Devi Parikh, Adriana Kovashka, Amar Parkash, Krist...
ACL
2010
13 years 7 months ago
Unsupervised Search for the Optimal Segmentation for Statistical Machine Translation
We tackle the previously unaddressed problem of unsupervised determination of the optimal morphological segmentation for statistical machine translation (SMT) and propose a segmen...
Coskun Mermer, Ahmet Afsn Akn