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ICML
2007
IEEE
16 years 7 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ICML
2007
IEEE
16 years 7 months ago
Dirichlet aggregation: unsupervised learning towards an optimal metric for proportional data
Proportional data (normalized histograms) have been frequently occurring in various areas, and they could be mathematically abstracted as points residing in a geometric simplex. A...
Hua-Yan Wang, Hongbin Zha, Hong Qin
213
Voted
ICRA
2003
IEEE
222views Robotics» more  ICRA 2003»
16 years 4 days ago
Path planning using learned constraints and preferences
— In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of ...
Gregory Dudek, Saul Simhon
COLT
2006
Springer
15 years 10 months ago
Online Learning with Variable Stage Duration
We consider online learning in repeated decision problems, within the framework of a repeated game against an arbitrary opponent. For repeated matrix games, well known results esta...
Shie Mannor, Nahum Shimkin
154
Voted
ATAL
2008
Springer
15 years 9 months ago
Non-linear dynamics in multiagent reinforcement learning algorithms
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Only a subset of these MARL algorithms both do not require agent...
Sherief Abdallah, Victor R. Lesser