157 citations · 546 across the 8 of their papers we have counts for
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cs.AI2012★ 54 cited
Value Function Approximation in Zero-Sum Markov Games
Michail Lagoudakis, Ron Parr
This paper investigates value function approximation in the context of zero-sum Markov games, which can be viewed as a generalization of the Markov decision process (MDP) framework…
cs.LG2012★ 6 cited
Value Function Approximation in Noisy Environments Using Locally Smoothed Regularized Approximate Linear Programs
Gavin Taylor, Ron Parr
Recently, Petrik et al. demonstrated that L1Regularized Approximate Linear Programming (RALP) could produce value functions and policies which compared favorably to established lin…
cs.CV2012
Efficient Selection of Disambiguating Actions for Stereo Vision
Monika Schaeffer, Ron Parr
In many domains that involve the use of sensors, such as robotics or sensor networks, there are opportunities to use some form of active sensing to disambiguate data from noisy or…