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AGENTS
1999
Springer
15 years 9 months ago
General Principles of Learning-Based Multi-Agent Systems
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
David Wolpert, Kevin R. Wheeler, Kagan Tumer
GECCO
2009
Springer
135views Optimization» more  GECCO 2009»
15 years 11 months ago
Neuroevolutionary reinforcement learning for generalized helicopter control
Helicopter hovering is an important challenge problem in the field of reinforcement learning. This paper considers several neuroevolutionary approaches to discovering robust cont...
Rogier Koppejan, Shimon Whiteson
ICCV
2009
IEEE
15 years 2 months ago
Learning to predict where humans look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable ...
Tilke Judd, Krista A. Ehinger, Frédo Durand...
ATAL
2005
Springer
15 years 10 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ENC
2004
IEEE
15 years 8 months ago
Distributed Learning in Intentional BDI Multi-Agent Systems
Despite the relevance of the belief-desire-intention (BDI) model of rational agency, little work has been done to deal with its two main limitations: the lack of learning competen...
Alejandro Guerra-Hernández, Amal El Fallah-...