2103 search results - page 146 / 421 » Approximate Learning of Dynamic Models |
152
click to vote
PKDD
2010
Springer
15 years 3 months ago
2010
Springer
Abstract. Bayesian reinforcement learning (RL) is aimed at making more efficient use of data samples, but typically uses significantly more computation. For discrete Markov Decis...
150
Voted
AI
2011
Springer
14 years 12 months ago
2011
Springer
Qualitative models are often a useful abstraction of the physical world. Learning qualitative models from numerical data sible way to obtain such an abstraction. We present a new ...
167
Voted
JAIR
2008
15 years 4 months ago
2008
Decision-theoretic planning is a popular approach to sequential decision making problems, because it treats uncertainty in sensing and acting in a principled way. In single-agent ...
162
click to vote
CA
1999
IEEE
15 years 9 months ago
1999
IEEE
This paper presents a simple and efficient method of modeling synthetic vision, memory, and learning for autonomous animated characters in real-time virtual environments. The mode...
208
Voted
AROBOTS
2011
14 years 12 months ago
2011
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...