115 search results - page 7 / 23 » Learning hierarchical task networks by observation |
WOA
2001
13 years 8 months ago
2001
Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
GECCO
2000
Springer
13 years 11 months ago
2000
Springer
Interactions between evolution and lifetime learning are of great interest to studies of adaptive behaviour both in the natural world and the field of evolutionary computation. Th...
ESANN
2007
13 years 9 months ago
2007
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
NIPS
1992
13 years 8 months ago
1992
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...