This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
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...
This paper proposed a kind of unsupervised learning neural network model, which has special structure and can realize an evaluation and classification of many groups by the compres...
— A method is presented for extending the Evolving Connectionist System (ECoS) algorithm that allows it to explicitly represent and learn nominal-scale data without the need for ...
Nodes in sensor fields and in autonomous swarms of mobile robots need to communicate; this usually requires individual nodes to either consume a significant amount of energy, ca...