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128
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AAAI
1993
15 years 5 months ago
Complexity Analysis of Real-Time Reinforcement Learning
This paper analyzes the complexity of on-line reinforcement learning algorithms, namely asynchronous realtime versions of Q-learning and value-iteration, applied to the problem of...
Sven Koenig, Reid G. Simmons
137
Voted
JITECH
2010
106views more  JITECH 2010»
15 years 2 months ago
Patterns and structures of intra-organizational learning networks within a knowledge-intensive organization
This paper employs the network perspective to study patterns and structures of intraorganizational learning networks. The theoretical background draws from cognitive theories, the...
Miha Skerlavaj, Vlado Dimovski, Kevin C. Desouza
151
Voted
ACL
2010
15 years 1 months ago
Learning to Adapt to Unknown Users: Referring Expression Generation in Spoken Dialogue Systems
We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to unde...
Srinivasan Janarthanam, Oliver Lemon
168
Voted
CVPR
2010
IEEE
15 years 1 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
134
Voted
NIPS
2007
15 years 5 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...