Sciweavers

2108 search results - page 61 / 422
» Tracking in Reinforcement Learning
Sort
View
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
14 years 1 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
ICML
2005
IEEE
14 years 10 months ago
Identifying useful subgoals in reinforcement learning by local graph partitioning
We present a new subgoal-based method for automatically creating useful skills in reinforcement learning. Our method identifies subgoals by partitioning local state transition gra...
Özgür Simsek, Alicia P. Wolfe, Andrew G....
IAT
2008
IEEE
13 years 10 months ago
Scaling Up Multi-agent Reinforcement Learning in Complex Domains
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
Dan Xiao, Ah-Hwee Tan
ICRA
2008
IEEE
141views Robotics» more  ICRA 2008»
14 years 4 months ago
Tracking interacting targets with laser scanner via on-line supervised learning
— Successful multi-target tracking requires locating the targets and labeling their identities. For the laser based tracking system, the latter becomes significantly more challen...
Xuan Song, Jinshi Cui, Xulei Wang, Huijing Zhao, H...
ATAL
2007
Springer
14 years 4 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone