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AUSAI
2004
Springer
14 years 3 months ago
A Dynamic Allocation Method of Basis Functions in Reinforcement Learning
In this paper, we propose a dynamic allocation method of basis functions, an Allocation/Elimination Gaussian Softmax Basis Function Network (AE-GSBFN), that is used in reinforcemen...
Shingo Iida, Kiyotake Kuwayama, Masayoshi Kanoh, S...
IAT
2010
IEEE
13 years 7 months ago
A Biologically-Inspired Cognitive Agent Model Integrating Declarative Knowledge and Reinforcement Learning
Abstract--The paper proposes a biologically-inspired cognitive agent model, known as FALCON-X, based on an integration of the Adaptive Control of Thought (ACT-R) architecture and a...
Ah-Hwee Tan, Gee Wah Ng
IJRR
2008
139views more  IJRR 2008»
13 years 9 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
AR
1998
106views more  AR 1998»
13 years 9 months ago
A cognitive robot architecture based on tactile and visual information
In this paper, we propose an architecture for a cognitive robot based on tactile and visual information. Visual information contains various features such as location and area of ...
Kazunori Terada, Takayuki Nakamura, Hideaki Takeda...
ATAL
2005
Springer
14 years 3 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson