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NIPS
2001
13 years 6 months ago
Model-Free Least-Squares Policy Iteration
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
Michail G. Lagoudakis, Ronald Parr
ICRA
2006
IEEE
131views Robotics» more  ICRA 2006»
13 years 11 months ago
Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Thomas Kollar, Nicholas Roy
AAAI
2007
13 years 7 months ago
Automated Online Mechanism Design and Prophet Inequalities
Recent work on online auctions for digital goods has explored the role of optimal stopping theory — particularly secretary problems — in the design of approximately optimal on...
Mohammad Taghi Hajiaghayi, Robert D. Kleinberg, Tu...
RTSS
2007
IEEE
13 years 11 months ago
A UML-Based Design Framework for Time-Triggered Applications
Time-triggered architectures (TTAs) are strong candidate platforms for safety-critical real-time applications. A typical time-triggered architecture is constituted by one or more ...
Kathy Dang Nguyen, P. S. Thiagarajan, Weng-Fai Won...