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AUTOMATICA
2007
124views more  AUTOMATICA 2007»
14 years 10 months ago
Motion planning in uncertain environments with vision-like sensors
In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
Suman Chakravorty, John L. Junkins
TSMC
2008
229views more  TSMC 2008»
14 years 9 months ago
A Comprehensive Survey of Multiagent Reinforcement Learning
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Lucian Busoniu, Robert Babuska, Bart De Schutter
JAIR
2010
145views more  JAIR 2010»
14 years 8 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint
WORDS
2003
IEEE
15 years 3 months ago
Foucault's Pendulum in the Distributed Control Lab
The ’Distributed Control Lab’ [6] at Hasso-PlattnerInstitute, University of Potsdam allows experimentation with a variety of physical equipment via the web (intra and internet...
Andreas Rasche, Peter Tröger, Michael Dirska,...
ATAL
2010
Springer
14 years 11 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls