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UAI
2001
15 years 8 months ago
The Optimal Reward Baseline for Gradient-Based Reinforcement Learning
There exist a number of reinforcement learning algorithms which learn by climbing the gradient of expected reward. Their long-run convergence has been proved, even in partially ob...
Lex Weaver, Nigel Tao
FLAIRS
1998
15 years 8 months ago
Optimizing Production Manufacturing Using Reinforcement Learning
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
Sridhar Mahadevan, Georgios Theocharous
AAAI
1994
15 years 8 months ago
Learning to Explore and Build Maps
Using the methods demonstrated in this paper, a robot with an unknown sensorimotor system can learn sets of features and behaviors adequate to explore a continuous environment and...
David Pierce, Benjamin Kuipers
IROS
2007
IEEE
179views Robotics» more  IROS 2007»
16 years 1 months ago
Incremental learning for place recognition in dynamic environments
Abstract— Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be ...
Jie Luo, Andrzej Pronobis, Barbara Caputo, Patric ...
SMC
2007
IEEE
125views Control Systems» more  SMC 2007»
16 years 1 months ago
A hierarchical strategy for learning of robot walking strategies in natural terrain environments
– In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surfa...
Ayanna M. Howard, Lonnie T. Parker