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JAIR
2002
163views more  JAIR 2002»
15 years 6 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
NECO
2007
150views more  NECO 2007»
15 years 6 months ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
STOC
2005
ACM
129views Algorithms» more  STOC 2005»
16 years 7 months ago
Learning with attribute costs
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
Haim Kaplan, Eyal Kushilevitz, Yishay Mansour
173
Voted
SBIA
2004
Springer
16 years 4 days ago
Learning with Drift Detection
Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Pedro Medas, Gladys Castillo, Pe...
GECCO
2010
Springer
184views Optimization» more  GECCO 2010»
15 years 11 months ago
Transfer learning through indirect encoding
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....
Phillip Verbancsics, Kenneth O. Stanley