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ICMLA
2010
13 years 7 months ago
Ensembles of Neural Networks for Robust Reinforcement Learning
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
Alexander Hans, Steffen Udluft
SEMWEB
2005
Springer
14 years 2 months ago
Ontology Learning and Reasoning - Dealing with Uncertainty and Inconsistency
Ontology Learning from text aims at generating domain ontologies from textual resources by applying natural language processing and machine learning techniques. It is inherent in t...
Peter Haase, Johanna Völker
AAI
2005
124views more  AAI 2005»
13 years 9 months ago
Lessons From Emotion Psychology For The Design Of Lifelike Characters
This special issue describes a number of applications that utilize lifelike characters that teach indirectly, by playing some role in a social interaction with a user. The design ...
Jonathan Gratch, Stacy Marsella
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
14 years 1 months ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh
COLT
2008
Springer
13 years 11 months ago
When Random Play is Optimal Against an Adversary
We analyze a sequential game between a Gambler and a Casino. The Gambler allocates bets from a limited budget over a fixed menu of gambling events that are offered at equal time i...
Jacob Abernethy, Manfred K. Warmuth, Joel Yellin