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NECO
2007
150views more  NECO 2007»
13 years 4 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
IIE
2007
63views more  IIE 2007»
13 years 5 months ago
Investigation of Q-Learning in the Context of a Virtual Learning Environment
We investigate the possibility to apply a known machine learning algorithm of Q-learning in the domain of a Virtual Learning Environment (VLE). It is important in this problem doma...
Dalia Baziukaite
IBERAMIA
2004
Springer
13 years 10 months ago
Mobile Robotic Supported Collaborative Learning (MRSCL)
In this paper we describe MRSCL Geometry a collaborative educational activity that explores the use of robotic technology and wirelessly connected Pocket PCs as tools for teaching ...
Rubén Mitnik, Miguel Nussbaum, Alvaro Soto
ICANN
2005
Springer
13 years 10 months ago
Evolving Modular Fast-Weight Networks for Control
Abstract. In practice, almost all control systems in use today implement some form of linear control. However, there are many tasks for which conventional control engineering metho...
Faustino J. Gomez, Jürgen Schmidhuber
IJRR
2008
139views more  IJRR 2008»
13 years 5 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal