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» Using Stochastic Grammars to Learn Robotic Tasks
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IROS
2006
IEEE
159views Robotics» more  IROS 2006»
15 years 10 months ago
Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing
— To operate outdoors or on non-flat surfaces, mobile robots need appropriate data structures that provide a compact representation of the environment and at the same time suppo...
Rudolph Triebel, Patrick Pfaff, Wolfram Burgard
AI
2008
Springer
15 years 4 months ago
The well-designed child
This article is inspired by recent psychological studies confirming that a child is not born a blank slate but has important innate capabilities. An important part of the "le...
John McCarthy
JAIR
2011
144views more  JAIR 2011»
14 years 11 months ago
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Mahdi Milani Fard, Joelle Pineau
ECCV
2004
Springer
16 years 6 months ago
Multiple View Feature Descriptors from Image Sequences via Kernel Principal Component Analysis
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...
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