425 search results - page 72 / 85 » Using Stochastic Grammars to Learn Robotic Tasks |
NLPRS
2001
Springer
13 years 12 months ago
2001
Springer
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
ICRA
2007
IEEE
14 years 1 months ago
2007
IEEE
— The exploration problem is a central issue in mobile robotics. A complete coverage is not practical if the environment is large with a few small hotspots, and the sampling cost...
AAAI
2011
12 years 7 months ago
2011
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
HICSS
2007
IEEE
14 years 1 months ago
2007
IEEE
— Bayesian networks play a key role in decision support within health care. Physicians rely on Bayesian networks to give medical treatment, generate what-if scenarios, and other ...
JMLR
2010
13 years 2 months ago
2010
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...