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» Algorithms for Inverse Reinforcement Learning
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PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
14 years 8 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
ICML
2000
IEEE
15 years 10 months ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
AIIDE
2008
15 years 2 days ago
Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...
CIS
2005
Springer
15 years 3 months ago
An RLS-Based Natural Actor-Critic Algorithm for Locomotion of a Two-Linked Robot Arm
Recently, actor-critic methods have drawn much interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy...
Jooyoung Park, Jongho Kim, Daesung Kang
ICML
2002
IEEE
15 years 10 months ago
Learning from Scarce Experience
Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
Leonid Peshkin, Christian R. Shelton