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» The Dynamics of Multi-Agent Reinforcement Learning
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NN
2006
Springer
140views Neural Networks» more  NN 2006»
14 years 9 months ago
Neural mechanism for stochastic behaviour during a competitive game
Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another...
Alireza Soltani, Daeyeol Lee, Xiao-Jing Wang
IROS
2007
IEEE
172views Robotics» more  IROS 2007»
15 years 3 months ago
Motor control optimization of compliant one-legged locomotion in rough terrain
— While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for ada...
Fumiya Iida, Russ Tedrake
ICMLA
2004
14 years 11 months ago
Planning with predictive state representations
Predictive state representation (PSR) models for controlled dynamical systems have recently been proposed as an alternative to traditional models such as partially observable Mark...
Michael R. James, Satinder P. Singh, Michael L. Li...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
14 years 4 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor
AINA
2006
IEEE
15 years 1 months ago
Constrained Flooding: A Robust and Efficient Routing Framework for Wireless Sensor Networks
Flooding protocols for wireless networks in general have been shown to be very inefficient and therefore are mainly used in network initialization or route discovery and maintenan...
Ying Zhang, Markus P. J. Fromherz