Michal Valko : Apprenticeship Learning

Apprenticeship Learning

Chronological list of key papers in apprenticeship learning and inverse reinforcement learning. These methods allow agents to learn behaviors by observing expert demonstrations.

Chronological list of apprenticeship learning papers

2015
Maximum Entropy Semi-Supervised Inverse Reinforcement Learning
Julien Audiffren, Michal Valko
IJCAI 2015
2013
Cascaded Inverse Reinforcement Learning
Robert Klein, Abdeslam Boularias, Gerhard Neumann, Oliver Kroemer, Jan Peters
Workshop 2013
2013
Apprenticeship Learning on Contextual Multi-Armed Bandits
Abdeslam Boularias, Oliver Kroemer, Jan Peters
Workshop 2013
2013
Learning from Demonstrations: Is It Worth Estimating a Reward Function?
Bilal Piot, Matthieu Geist, Olivier Pietquin
ECML 2013
2012
Semi-Supervised Apprenticeship Learning
Michal Valko, Mohammad Ghavamzadeh, Alessandro Lazaric
EWRL 2012
2012
Active Imitation Learning via Reduction to I.I.D. Active Learning
Kshitij Judah, Saikat Roy, Alan Fern, Thomas Dietterich
UAI 2012
2012
Probabilistic Prediction and Interactive Decision-Making
Brian Ziebart
PhD Thesis 2012
2012
Nonparametric Bayesian Inverse Reinforcement Learning
Jaedeug Choi, Kee-Eung Kim
Machine Learning 2012
2012
Imitation Learning by Coaching
Michael He, Yuval Tassa, Drew Bagnell
NIPS 2012
2012
Algorithms for Reward Learning from Demonstrations
Abdeslam Boularias
PhD Thesis 2012
2012
Continuous Inverse Optimal Control with Locally Optimal Examples
Sergey Levine, Zoran Popović, Vladlen Koltun
ICML 2012
2011
MAP Inference for Bayesian Inverse Reinforcement Learning
Jaedeug Choi, Kee-Eung Kim
NIPS 2011
2011
Nonlinear Inverse Reinforcement Learning with Gaussian Processes
Sergey Levine, Vladlen Koltun
NIPS 2011
2011
Relative Entropy Inverse Reinforcement Learning
Abdeslam Boularias, Jens Kober, Jan Peters
AISTATS 2011
2010
An Analysis of Reinforcement Learning with Function Approximation
Francisco S. Melo, Isabel Ribeiro
ICML 2010
2010
Efficient Reductions for Imitation Learning
Drew Bagnell
AISTATS 2010
2010
A Reduction of Imitation Learning to No-Regret Online Learning
Stéphane Ross, Drew Bagnell
AISTATS 2010
2010
Feature Construction for Inverse Reinforcement Learning
Sergey Levine, Vladlen Koltun
NIPS 2010
2010
Inverse Optimal Control with Linearly-Solvable MDPs
Krishnamurthy Dvijotham, Emanuel Todorov
ICML 2010
2008
Maximum Entropy Inverse Reinforcement Learning
Brian Ziebart, Andrew Maas, Drew Bagnell, Anind Dey
AAAI 2008
2008
A Game-Theoretic Approach to Apprenticeship Learning
Umar Syed, Robert Schapire
NIPS 2008
2007
Learning to Search: Functional Gradient Techniques for Imitation Learning
Nathan Ratliff, David Silver, Drew Bagnell
Autonomous Robots 2007
2007
Apprenticeship Learning using Inverse Reinforcement Learning and Gradient Methods
Gergely Neu, Csaba Szepesvári
UAI 2007
2007
Bayesian Inverse Reinforcement Learning
Deepak Ramachandran, Eyal Amir
IJCAI 2007
2006
Maximum Margin Planning
Nathan Ratliff, Drew Bagnell, Martin Zinkevich
ICML 2006
2004
Apprenticeship Learning via Inverse Reinforcement Learning
Pieter Abbeel, Andrew Ng
ICML 2004
2000
Algorithms for Inverse Reinforcement Learning
Andrew Ng, Stuart Russell
ICML 2000
1998
Learning agents for uncertain environments
Stuart Russell
COLT 1998
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