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AAAI
2011
12 years 9 months ago
Value Function Approximation in Reinforcement Learning Using the Fourier Basis
We describe the Fourier Basis, a linear value function approximation scheme based on the Fourier Series. We empirically evaluate its properties, and demonstrate that it performs w...
George Konidaris, Sarah Osentoski, Philip Thomas
ICANN
2009
Springer
14 years 3 months ago
Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning
Model complexity is key concern to any artificial learning system due its critical impact on generalization. However, EC research has only focused phenotype structural complexity ...
Faustino J. Gomez, Julian Togelius, Jürgen Sc...
SCIA
2005
Springer
211views Image Analysis» more  SCIA 2005»
14 years 2 months ago
Perception-Action Based Object Detection from Local Descriptor Combination and Reinforcement Learning
This work proposes to learn visual encodings of attention patterns that enables sequential attention for object detection in real world environments. The system embeds a saccadic d...
Lucas Paletta, Gerald Fritz, Christin Seifert
FLAIRS
2004
13 years 10 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
NIPS
1993
13 years 10 months ago
The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces
Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensionalcontinuousstate-spaces. In high dimensions it is essential that learningdoes not...
Andrew W. Moore