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CORR
1998
Springer
164views Education» more  CORR 1998»
13 years 8 months ago
Training Reinforcement Neurocontrollers Using the Polytope Algorithm
A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorit...
Aristidis Likas, Isaac E. Lagaris
ESANN
2006
13 years 10 months ago
Reducing policy degradation in neuro-dynamic programming
We focus on neuro-dynamic programming methods to learn state-action value functions and outline some of the inherent problems to be faced, when performing reinforcement learning in...
Thomas Gabel, Martin Riedmiller
AIIDE
2008
13 years 11 months ago
Learning to be a Bot: Reinforcement Learning in Shooter Games
This paper demonstrates the applicability of reinforcement learning for first person shooter bot artificial intelligence. Reinforcement learning is a machine learning technique wh...
Michelle McPartland, Marcus Gallagher
NECO
2002
105views more  NECO 2002»
13 years 8 months ago
Multiple Model-Based Reinforcement Learning
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...
Kenji Doya, Kazuyuki Samejima, Ken-ichi Katagiri, ...
ICML
1996
IEEE
14 years 21 days ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos