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ECML
2006
Springer
15 years 10 months ago
Approximate Policy Iteration for Closed-Loop Learning of Visual Tasks
Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
Sébastien Jodogne, Cyril Briquet, Justus H....
ALT
2011
Springer
14 years 6 months ago
On Noise-Tolerant Learning of Sparse Parities and Related Problems
We consider the problem of learning sparse parities in the presence of noise. For learning parities on r out of n variables, we give an algorithm that runs in time poly log 1 δ , ...
Elena Grigorescu, Lev Reyzin, Santosh Vempala
PATAT
2004
Springer
130views Education» more  PATAT 2004»
16 years 7 days ago
Learning User Preferences in Distributed Calendar Scheduling
Abstract. Within the field of software agents, there has been increasing interest in automating the process of calendar scheduling in recent years. Calendar (or meeting) schedulin...
Jean Oh, Stephen F. Smith
FLAIRS
2008
15 years 9 months ago
State Space Compression with Predictive Representations
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
ICRA
2010
IEEE
147views Robotics» more  ICRA 2010»
15 years 5 months ago
Learning physically-instantiated game play through visual observation
Abstract— We present an integrated vision and robotic system that plays, and learns to play, simple physically-instantiated board games that are variants of TIC TAC TOE and HEXAP...
Andrei Barbu, Siddharth Narayanaswamy, Jeffrey Mar...