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» Probabilistic Planning in the Graphplan Framework
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CVPR
2004
IEEE
14 years 10 months ago
Fast, Integrated Person Tracking and Activity Recognition with Plan-View Templates from a Single Stereo Camera
Copyright 2004 IEEE. Published in Conference on Computer Vision and Pattern Recognition (CVPR-2004), June 27 - July 2, 2004, Washington DC. Personal use of this material is permit...
Michael Harville, Dalong Li
ATAL
2006
Springer
14 years 15 days ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
AIPS
2008
13 years 11 months ago
HiPPo: Hierarchical POMDPs for Planning Information Processing and Sensing Actions on a Robot
Flexible general purpose robots need to tailor their visual processing to their task, on the fly. We propose a new approach to this within a planning framework, where the goal is ...
Mohan Sridharan, Jeremy L. Wyatt, Richard Dearden
IJCAI
2007
13 years 10 months ago
A Hybridized Planner for Stochastic Domains
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Mausam, Piergiorgio Bertoli, Daniel S. Weld
IJRR
2011
218views more  IJRR 2011»
13 years 3 months ago
Motion planning under uncertainty for robotic tasks with long time horizons
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...