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ESANN
2004
13 years 9 months ago
High-accuracy value-function approximation with neural networks applied to the acrobot
Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
Rémi Coulom
ICML
2010
IEEE
13 years 8 months ago
Toward Off-Policy Learning Control with Function Approximation
We present the first temporal-difference learning algorithm for off-policy control with unrestricted linear function approximation whose per-time-step complexity is linear in the ...
Hamid Reza Maei, Csaba Szepesvári, Shalabh ...
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
NIPS
2008
13 years 9 months ago
Regularized Policy Iteration
In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
NIPS
2007
13 years 9 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...