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IAT
2005
IEEE
15 years 10 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu
GECCO
2005
Springer
152views Optimization» more  GECCO 2005»
15 years 10 months ago
GAMM: genetic algorithms with meta-models for vision
Recent adaptive image interpretation systems can reach optimal performance for a given domain via machine learning, without human intervention. The policies are learned over an ex...
Greg Lee, Vadim Bulitko
GECCO
2004
Springer
114views Optimization» more  GECCO 2004»
15 years 9 months ago
Evolutionary Drug Scheduling Model for Cancer Chemotherapy
This paper presents a modified optimal control model of drug scheduling in cancer chemotherapy and a new adaptive elitist-population based genetic algorithm (AEGA) to solve it. Wo...
Yong Liang, Kwong-Sak Leung, Tony Shu Kam Mok
ECML
2003
Springer
15 years 9 months ago
Could Active Perception Aid Navigation of Partially Observable Grid Worlds?
Due to the unavoidable fact that a robot’s sensors will be limited in some manner, it is entirely possible that it can find itself unable to distinguish between differing state...
Paul A. Crook, Gillian Hayes
FSR
2003
Springer
94views Robotics» more  FSR 2003»
15 years 9 months ago
Planning under Uncertainty for Reliable Health Care Robotics
We describe a mobile robot system, designed to assist residents of an retirement facility. This system is being developed to respond to an aging population and a predicted shortage...
Nicholas Roy, Geoffrey J. Gordon, Sebastian Thrun