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ATAL
2005
Springer
15 years 5 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
RSS
2007
151views Robotics» more  RSS 2007»
15 years 1 months ago
An Implicit Time-Stepping Method for Multibody Systems with Intermittent Contact
— In this paper we present an implicit time-stepping scheme for multibody systems with intermittent contact by incorporating the contact constraints as a set of complementarity a...
Nilanjan Chakraborty, Stephen Berard, Srinivas Ake...
COCO
1994
Springer
140views Algorithms» more  COCO 1994»
15 years 4 months ago
Random Debaters and the Hardness of Approximating Stochastic Functions
A probabilistically checkable debate system (PCDS) for a language L consists of a probabilisticpolynomial-time veri er V and a debate between Player 1, who claims that the input x ...
Anne Condon, Joan Feigenbaum, Carsten Lund, Peter ...
ICMLA
2008
15 years 1 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux
BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 1 days ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo