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AAAI
2006
13 years 9 months ago
Learning Representation and Control in Continuous Markov Decision Processes
This paper presents a novel framework for simultaneously learning representation and control in continuous Markov decision processes. Our approach builds on the framework of proto...
Sridhar Mahadevan, Mauro Maggioni, Kimberly Fergus...
ECSQARU
2003
Springer
14 years 24 days ago
A Representation Theorem and Applications
We introduce a set of transformations on the set of all probability distributions over a finite state space, and show that these transformations are the only ones that preserve c...
Manfred Jaeger
IJCAI
2003
13 years 9 months ago
Action representation and partially observable planning using epistemic logic
We propose a purely logical framework for planning in partially observable environments. Knowledge states are expressed in a suitable fragment of the epistemic logic S5. We show h...
Andreas Herzig, Jérôme Lang, Pierre M...
SOFSEM
2012
Springer
12 years 3 months ago
Turing Machines for Dummies - Why Representations Do Matter
Abstract. Various methods exists in the literature for denoting the configuration of a Turing Machine. A key difference is whether the head position is indicated by some integer ...
Peter van Emde Boas
CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic