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ATAL
2007
Springer
14 years 3 months ago
IFSA: incremental feature-set augmentation for reinforcement learning tasks
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Mazda Ahmadi, Matthew E. Taylor, Peter Stone
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
14 years 2 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang
ICANN
2005
Springer
14 years 2 months ago
Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines
Although Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems, they suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
NIPS
1998
13 years 10 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
JIRS
2000
133views more  JIRS 2000»
13 years 9 months ago
Managing Complexity in Large Learning Robotic Systems
Abstract. Autonomous learning systems of significant complexity often consist of several interacting modules or agents. These modules collaborate to produce a system which, when vi...
Kynan Eng, Alec P. Robertson, Deane R. Blackman