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COLT
2006
Springer
15 years 7 months ago
Online Learning with Constraints
In this paper, we study a sequential decision making problem. The objective is to maximize the total reward while satisfying constraints, which are defined at every time step. The...
Shie Mannor, John N. Tsitsiklis
IJCNN
2000
IEEE
15 years 8 months ago
A Constraint Learning Algorithm for Blind Source Separation
In Jutten’s blind separation algorithm, symmetrical distribution and statistical independence of the signal sources are assumed. When they are not satisfied, the learning proce...
Kenji Nakayama, Akihiro Hirano, Motoki Nitta
ACMIDC
2009
15 years 7 months ago
Designing for physical-digital correspondence in tangible learning environments
In tangible learning environments the potential to exploit different physical-digital links increases representational power but also broadens the complexity of design. This paper...
Sara Price, Taciana Pontual Falcão
IJSNET
2006
145views more  IJSNET 2006»
15 years 3 months ago
RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks
:This paper introduces RL-MAC, a novel adaptive MediaAccess Control (MAC) protocol for Wireless Sensor Networks (WSN) that employs a reinforcement learning framework. Existing sche...
Zhenzhen Liu, Itamar Elhanany
ATAL
2010
Springer
15 years 4 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