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» Compositional Models for Reinforcement Learning
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ATAL
2011
Springer
12 years 7 months ago
Using iterated reasoning to predict opponent strategies
The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
QRE
2010
129views more  QRE 2010»
13 years 6 months ago
Improving quality of prediction in highly dynamic environments using approximate dynamic programming
In many applications, decision making under uncertainty often involves two steps- prediction of a certain quality parameter or indicator of the system under study and the subseque...
Rajesh Ganesan, Poornima Balakrishna, Lance Sherry
AAAI
2011
12 years 7 months ago
Understanding Natural Language Commands for Robotic Navigation and Mobile Manipulation
This paper describes a new model for understanding natural language commands given to autonomous systems that perform navigation and mobile manipulation in semi-structured environ...
Stefanie Tellex, Thomas Kollar, Steven Dickerson, ...
COLCOM
2005
IEEE
14 years 1 months ago
Developing a framework for integrating prior problem solving and knowledge sharing histories of a group to predict future group
Using a combination of machine learning probabilistic tools, we have shown that some chemistry students fail to develop productive problem solving strategies through practice alon...
Ron Stevens, Amy Soller, Alessandra Giordani, Luca...
CVPR
2010
IEEE
14 years 4 months ago
Warping Background Subtraction
We present a background model that differentiates between background motion and foreground objects. Unlike most models that represent the variability of pixel intensity at a partic...
Teresa Ko, Stefano Soatto, Deborah Estrin