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GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
13 years 11 months ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
WWW
2007
ACM
14 years 8 months ago
Learning information intent via observation
Workers in organizations frequently request help from assistants by sending request messages that express information intent: an intention to update data in an information system....
Anthony Tomasic, Isaac Simmons, John Zimmerman
ISCA
2006
IEEE
138views Hardware» more  ISCA 2006»
14 years 1 months ago
Learning-Based SMT Processor Resource Distribution via Hill-Climbing
The key to high performance in Simultaneous Multithreaded (SMT) processors lies in optimizing the distribution of shared resources to active threads. Existing resource distributio...
Seungryul Choi, Donald Yeung
IJCNN
2008
IEEE
14 years 2 months ago
Adaptive curiosity for emotions detection in speech
— Exploratory activities seem to be crucial for our cognitive development. According to psychologists, exploration is an intrinsically rewarding behaviour. The developmental robo...
Alexis Bondu, Vincent Lemaire
IJCM
2008
93views more  IJCM 2008»
13 years 7 months ago
A reinforced learning control using iterative error compensation for uncertain dynamical systems
This paper investigates a learning control using iterative error compensation for uncertain systems to enhance the precision of high speed, computer controlled machining process. ...
Kuei-Shu Hsu, Wen-Shyong Yu, Ming-In Ho