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ICML
2007
IEEE
14 years 8 months ago
Bayesian actor-critic algorithms
We1 present a new actor-critic learning model in which a Bayesian class of non-parametric critics, using Gaussian process temporal difference learning is used. Such critics model ...
Mohammad Ghavamzadeh, Yaakov Engel
NIPS
1998
13 years 9 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore
ANLP
1992
116views more  ANLP 1992»
13 years 9 months ago
Automatic Learning for Semantic Collocation
The real di culty in development of practical NLP systems comes from the fact that we do not have e ective means for gathering \knowledge". In this paper, we propose an algor...
Satoshi Sekine, Jeremy J. Carroll, Sophia Ananiado...
IJHIS
2006
94views more  IJHIS 2006»
13 years 8 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
SIGECOM
2010
ACM
149views ECommerce» more  SIGECOM 2010»
14 years 23 days ago
A new understanding of prediction markets via no-regret learning
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Yiling Chen, Jennifer Wortman Vaughan