132 search results - page 14 / 27 » Generalization in Reinforcement Learning: Safely Approximati... |
CORR
2010
Springer
14 years 11 months ago
2010
Springer
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
82
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ICMLA
2007
15 years 1 months ago
2007
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
86
Voted
ECML
2006
Springer
15 years 3 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
108
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UAI
2008
15 years 1 months ago
2008
Continuous state spaces and stochastic, switching dynamics characterize a number of rich, realworld domains, such as robot navigation across varying terrain. We describe a reinfor...
83
Voted
ECML
2007
Springer
15 years 5 months ago
2007
Springer
A general game player is an agent capable of taking as input a description of a game’s rules in a formal language and proceeding to play without any subsequent human input. To do...