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GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
12 years 8 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
SIGIR
2002
ACM
13 years 4 months ago
Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering
A novel method for simultaneous keyphrase extraction and generic text summarization is proposed by modeling text documents as weighted undirected and weighted bipartite graphs. Sp...
Hongyuan Zha
DSL
2009
13 years 3 months ago
Operator Language: A Program Generation Framework for Fast Kernels
Abstract. We present the Operator Language (OL), a framework to automatically generate fast numerical kernels. OL provides the structure to extend the program generation system Spi...
Franz Franchetti, Frédéric de Mesmay...
IJCNN
2006
IEEE
13 years 11 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal
COR
2008
164views more  COR 2008»
13 years 5 months ago
Observations in using parallel and sequential evolutionary algorithms for automatic software testing
In this paper we analyze the application of parallel and sequential evolutionary algorithms (EAs) to the automatic test data generation problem. The problem consists of automatica...
Enrique Alba, J. Francisco Chicano