1270 search results - page 193 / 254 » Dogged Learning for Robots |
98
Voted
TSMC
2002
15 years 3 months ago
2002
In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learn...
136
Voted
ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
145
Voted
AIIA
2007
Springer
15 years 9 months ago
2007
Springer
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
93
Voted
ICONIP
2009
15 years 1 months ago
2009
Abstract. Wild rodents learn the danger-predicting meaning of predator bird calls through the paring of cues which are an aversive stimulus (immediate danger signal or unconditione...
142
Voted
ICAS
2009
IEEE
15 years 10 months ago
2009
IEEE
Abstract—Traditionally, performance has been the most important metrics when evaluating a system. However, in the last decades industry and academia have been paying increasing a...