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IJRR
2008
186views more  IJRR 2008»
13 years 4 months 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...
CEC
2007
IEEE
13 years 11 months ago
Combine and compare evolutionary robotics and reinforcement Learning as methods of designing autonomous robots
—The purpose of this paper is to present a comparison between two methods of building adaptive controllers for robots. In spite of the wide range of techniques which are used for...
Sergiu Goschin, Eduard Franti, Monica Dascalu, San...
CIIA
2009
13 years 5 months ago
Dynamic Scheduling in Petroleum Process using Reinforcement Learning
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
Nassima Aissani, Bouziane Beldjilali
GECCO
2008
Springer
138views Optimization» more  GECCO 2008»
13 years 5 months ago
Modular neuroevolution for multilegged locomotion
Legged robots are useful in tasks such as search and rescue because they can effectively navigate on rugged terrain. However, it is difficult to design controllers for them that ...
Vinod K. Valsalam, Risto Miikkulainen
EUSFLAT
2001
144views Fuzzy Logic» more  EUSFLAT 2001»
13 years 6 months ago
Adaptive torque control using a connectionist reinforcement learning agent
The correction of angular misalignment between mating components is a fundamental requirement for their successful assembly. In this paper we present how a learning agent based on...
Lorenzo Brignone, Martin Howarth, S. Sivayoganatha...