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ICANNGA
2007
Springer
153views Algorithms» more  ICANNGA 2007»
15 years 6 months ago
A Neural Framework for Robot Motor Learning Based on Memory Consolidation
Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from se...
Heni Ben Amor, Shuhei Ikemoto, Takashi Minato, Ber...
IJCAI
2007
15 years 6 months ago
Memory-Bounded Dynamic Programming for DEC-POMDPs
Decentralized decision making under uncertainty has been shown to be intractable when each agent has different partial information about the domain. Thus, improving the applicabil...
Sven Seuken, Shlomo Zilberstein
CONNECTION
2004
98views more  CONNECTION 2004»
15 years 4 months ago
Self-refreshing memory in artificial neural networks: learning temporal sequences without catastrophic forgetting
While humans forget gradually, highly distributed connectionist networks forget catastrophically: newly learned information often completely erases previously learned information. ...
Bernard Ans, Stephane Rousset, Robert M. French, S...
TVLSI
2008
150views more  TVLSI 2008»
15 years 4 months ago
Data Memory Subsystem Resilient to Process Variations
As technology scales, more sophisticated fabrication processes cause variations in many different parameters in the device. These variations could severely affect the performance o...
M. Bennaser, Yao Guo, Csaba Andras Moritz
ICONIP
2010
15 years 3 months ago
Learning Shapes Bifurcations of Neural Dynamics upon External Stimuli
Memory is often considered to be embedded into one of the attractors in neural dynamical systems, which provides an appropriate output depending on the initial state specified by ...
Tomoki Kurikawa, Kunihiko Kaneko