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ICML
1994
IEEE
15 years 10 months ago
Markov Games as a Framework for Multi-Agent Reinforcement Learning
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
Michael L. Littman
MOBISYS
2006
ACM
16 years 6 months ago
Context-aware interactive content adaptation
Automatic adaptation of content for mobile devices is a challenging problem because optimal adaptation often depends on the usage semantics of content, as well as the context of u...
Iqbal Mohomed, Jim Chengming Cai, Sina Chavoshi, E...
EMO
2009
Springer
159views Optimization» more  EMO 2009»
16 years 1 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel
ECML
2003
Springer
15 years 11 months ago
Ensembles of Multi-instance Learners
In multi-instance learning, the training set comprises labeled bags that are composed of unlabeled instances, and the task is to predict the labels of unseen bags. Through analyzin...
Zhi-Hua Zhou, Min-Ling Zhang
SAC
2005
ACM
16 years 2 days ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra