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» On Weak Markov's Principle
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COGSCI
2007
99views more  COGSCI 2007»
13 years 7 months ago
Language Evolution by Iterated Learning With Bayesian Agents
Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that la...
Thomas L. Griffiths, Michael L. Kalish
AML
2002
94views more  AML 2002»
13 years 7 months ago
H-theories, fragments of HA and PA-normality
For a classical theory T, H(T) denotes the intuitionistic theory of T-normal (i.e. locally T) Kripke structures. S. Buss has asked for a characterization of the theories in the ra...
Morteza Moniri
JMLR
2002
133views more  JMLR 2002»
13 years 7 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
PKDD
2010
Springer
129views Data Mining» more  PKDD 2010»
13 years 6 months ago
Smarter Sampling in Model-Based Bayesian Reinforcement Learning
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
Pablo Samuel Castro, Doina Precup
GLOBECOM
2010
IEEE
13 years 5 months ago
Cooperation Stimulation in Cognitive Networks Using Indirect Reciprocity Game Modelling
In cognitive networks, since nodes generally belong to different authorities and pursue different goals, they will not cooperate with others unless cooperation can improve their ow...
Yan Chen, K. J. Ray Liu