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ICTAI
2006
IEEE
15 years 3 months ago
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents
In order for an autonomous agent to behave robustly in a variety of environments, it must have the ability to learn approximations to many different functions. The function approx...
Daniel Stronger, Peter Stone
AAAI
2011
13 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
ICML
1995
IEEE
15 years 10 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
JACIII
2007
99views more  JACIII 2007»
14 years 9 months ago
Asymptotic Behavior of Linear Approximations of Pseudo-Boolean Functions
We study the problem of approximating pseudoBoolean functions by linear pseudo-Boolean functions. Pseudo-Boolean functions generalize ordinary Boolean functions by allowing the fu...
Guoli Ding, Robert F. Lax, Peter P. Chen, Jianhua ...
GECCO
2007
Springer
139views Optimization» more  GECCO 2007»
15 years 3 months ago
The role of speciation in spatial coevolutionary function approximation
The role of space is more and more accepted as a way to dramatically improve the success of coevolutionary function approximation. The process behind this success however is not y...
Folkert de Boer, Paulien Hogeweg