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» Algorithms for Inverse Reinforcement Learning
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IDA
2007
Springer
15 years 3 months ago
Learning to Align: A Statistical Approach
We present a new machine learning approach to the inverse parametric sequence alignment problem: given as training examples a set of correct pairwise global alignments, find the p...
Elisa Ricci, Tijl De Bie, Nello Cristianini
IJRR
2011
126views more  IJRR 2011»
14 years 4 months ago
Optimization and learning for rough terrain legged locomotion
We present a novel approach to legged locomotion over rough terrain that is thoroughly rooted in optimization. This approach relies on a hierarchy of fast, anytime algorithms to p...
Matthew Zucker, Nathan D. Ratliff, Martin Stolle, ...
ECML
2006
Springer
15 years 1 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....
ICML
2008
IEEE
15 years 10 months ago
Learning all optimal policies with multiple criteria
We describe an algorithm for learning in the presence of multiple criteria. Our technique generalizes previous approaches in that it can learn optimal policies for all linear pref...
Leon Barrett, Srini Narayanan
ADHOCNETS
2010
Springer
14 years 6 months ago
DCLA: A Duty-Cycle Learning Algorithm for IEEE 802.15.4 Beacon-Enabled WSNs
The current specification for IEEE 802.15.4 beacon-enabled networks does not define how active and sleep schedules should be configured in order to achieve the optimal network perf...
Rodolfo de Paz Alberola, Dirk Pesch