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IJRR
2008
186views more  IJRR 2008»
15 years 14 days ago
Automated Design of Adaptive Controllers for Modular Robots using Reinforcement Learning
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Paulina Varshavskaya, Leslie Pack Kaelbling, Danie...
93
Voted
ICASSP
2009
IEEE
15 years 7 months ago
Active learning for semi-supervised multi-task learning
We present an algorithm for active learning (adaptive selection of training data) within the context of semi-supervised multi-task classifier design. The semi-supervised multi-ta...
Hui Li, Xuejun Liao, Lawrence Carin
121
Voted
GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
15 years 4 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
113
Voted
JIRS
2010
120views more  JIRS 2010»
14 years 11 months ago
Designing Decentralized Controllers for Distributed-Air-Jet MEMS-Based Micromanipulators by Reinforcement Learning
Distributed-air-jet MEMS-based systems have been proposed to manipulate small parts with high velocities and without any friction problems. The control of such distributed systems ...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
91
Voted
CHI
2007
ACM
16 years 26 days ago
Localized iterative design for language learning in underdeveloped regions: the PACE framework
Poor literacy remains a decisive barrier to the economic empowerment of many people in the developing world. Of particular importance is literacy in a widely spoken "world la...
Matthew Kam, Divya Ramachandran, Varun Devanathan,...