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EUSFLAT
2001
144views Fuzzy Logic» more  EUSFLAT 2001»
13 years 5 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...
IJCNN
2007
IEEE
13 years 10 months ago
Adaptive Dynamic Modularity in a Connectionist Model of Context-Dependent Idea Generation
Abstract— Cognitive control - the ability to produce appropriate behavior in complex situations - is a fundamental aspect of intelligence. It is increasingly evident that this co...
Simona Doboli, Ali A. Minai, Vincent R. Brown
AGI
2011
12 years 8 months ago
Reinforcement Learning and the Bayesian Control Rule
We present an actor-critic scheme for reinforcement learning in complex domains. The main contribution is to show that planning and I/O dynamics can be separated such that an intra...
Pedro Alejandro Ortega, Daniel Alexander Braun, Si...
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...
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