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ICML
2007
IEEE
14 years 9 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ATAL
2010
Springer
13 years 10 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
IROS
2009
IEEE
145views Robotics» more  IROS 2009»
14 years 3 months ago
Utilizing prior information to enhance self-supervised aerial image analysis for extracting parking lot structures
Abstract— Road network information (RNI) simplifies autonomous driving by providing strong priors about driving environments. Its usefulness has been demonstrated in the DARPA U...
Young-Woo Seo, Chris Urmson
ATAL
2005
Springer
14 years 2 months ago
Extending the recognition-primed decision model to support human-agent collaboration
There has been much research investigating team cognition, naturalistic decision making, and collaborative technology as it relates to real world, complex domains of practice. How...
Xiaocong Fan, Shuang Sun, Michael D. McNeese, John...
AVI
2006
13 years 10 months ago
The ASPICE project: inclusive design for the motor disabled
The ASPICE project aims at the development of a system which allows the neuromotor disabled persons to improve or recover their mobility (directly or by emulation) and communicati...
Fabio Aloise, Febo Cincotti, Fabio Babiloni, Maria...