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» Learning by Experience Networks in Learning Organizations
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110
Voted
NN
1998
Springer
117views Neural Networks» more  NN 1998»
15 years 7 days ago
Neural learning of embodied interaction dynamics
This paper presents our approach towards realizing a robot which can bootstrap itself towards higher complexity through embodied interaction dynamics with the environment includin...
Yasuo Kuniyoshi, Luc Berthouze
121
Voted
ICML
2009
IEEE
16 years 1 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
96
Voted
ECAL
2007
Springer
15 years 6 months ago
The Dynamics of Associative Learning in an Evolved Situated Agent
Abstract. Artificial agents controlled by dynamic recurrent node networks with fixed weights are evolved to search for food and associate it with one of two different temperatur...
Eduardo Izquierdo, Inman Harvey
116
Voted
ITS
2010
Springer
178views Multimedia» more  ITS 2010»
15 years 5 months ago
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data
The traditional, well established approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pretest and posttest desig...
Zachary A. Pardos, Matthew D. Dailey, Neil T. Heff...
117
Voted
APIN
2004
116views more  APIN 2004»
15 years 14 days ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp