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84
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ICML
2000
IEEE
16 years 13 days ago
Reinforcement Learning in POMDP's via Direct Gradient Ascent
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
Jonathan Baxter, Peter L. Bartlett
CAEPIA
2011
Springer
13 years 11 months ago
Evaluating a Reinforcement Learning Algorithm with a General Intelligence Test
In this paper we apply the recent notion of anytime universal intelligence tests to the evaluation of a popular reinforcement learning algorithm, Q-learning. We show that a general...
Javier Insa-Cabrera, David L. Dowe, José He...
89
Voted
IJCAI
2003
15 years 1 months ago
Covariant Policy Search
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
J. Andrew Bagnell, Jeff G. Schneider
IROS
2007
IEEE
132views Robotics» more  IROS 2007»
15 years 6 months ago
Hysteretic q-learning : an algorithm for decentralized reinforcement learning in cooperative multi-agent teams
— Multi-agent systems (MAS) are a field of study of growing interest in a variety of domains such as robotics or distributed controls. The article focuses on decentralized reinf...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
ICMLA
2007
15 years 1 months ago
Control of a re-entrant line manufacturing model with a reinforcement learning approach
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...
José A. Ramírez-Hernández, Em...