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AAMAS
2007
Springer
13 years 7 months ago
Shaping multi-agent systems with gradient reinforcement learning
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...
Olivier Buffet, Alain Dutech, François Char...
ECCV
2006
Springer
14 years 9 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee
ATAL
2007
Springer
14 years 1 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
ICRA
2003
IEEE
116views Robotics» more  ICRA 2003»
14 years 29 days ago
Learning to role-switch in multi-robot systems
We present an approach that uses Q-learning on individual robotic agents, for coordinating a missiontasked team of robots in a complex scenario. To reduce the size of the state sp...
Eric Martinson, Ronald C. Arkin
CEC
2010
IEEE
12 years 11 months ago
Co-evolutionary search path planning under constrained information-sharing for a cooperative unmanned aerial vehicle team
—Mobile cooperative sensor networks are increasingly used for surveillance and reconnaissance tasks to support domain picture compilation. However, efficient distributed informat...
Jean Berger, Jens Happe