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IJCAI
2001
15 years 6 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
CEC
2008
IEEE
15 years 11 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
CSL
2010
Springer
15 years 5 months ago
Exact Exploration and Hanging Algorithms
Abstract. Recent analysis of sequential algorithms resulted in their axiomatization and in a representation theorem stating that, for any sealgorithm, there is an abstract state ma...
Andreas Blass, Nachum Dershowitz, Yuri Gurevich
CORR
2008
Springer
227views Education» more  CORR 2008»
15 years 4 months ago
An experimental analysis of Lemke-Howson algorithm
We present an experimental investigation of the performance of the Lemke-Howson algorithm, which is the most widely used algorithm for the computation of a Nash equilibrium for bi...
Bruno Codenotti, Stefano De Rossi, Marino Pagan
ICML
2008
IEEE
16 years 5 months ago
Estimating local optimums in EM algorithm over Gaussian mixture model
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung