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» Efficient Approximation of Optimal Control for Markov Games
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AMAI
2004
Springer
15 years 2 months ago
A Framework for Sequential Planning in Multi-Agent Settings
This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
Piotr J. Gmytrasiewicz, Prashant Doshi
CVPR
2007
IEEE
15 years 11 months ago
Efficient MRF Deformation Model for Non-Rigid Image Matching
We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displace...
Alexander Shekhovtsov, Ivan Kovtun, Václav ...
120
Voted
JMLR
2010
148views more  JMLR 2010»
14 years 4 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
68
Voted
ICML
2000
IEEE
15 years 10 months ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
NIPS
2001
14 years 10 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...