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ICRA
2003
IEEE
222views Robotics» more  ICRA 2003»
15 years 3 months ago
Path planning using learned constraints and preferences
— In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of ...
Gregory Dudek, Saul Simhon
PRICAI
2000
Springer
15 years 1 months ago
Generating Hierarchical Structure in Reinforcement Learning from State Variables
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
Bernhard Hengst
JMLR
2006
108views more  JMLR 2006»
14 years 9 months ago
Learning Spectral Clustering, With Application To Speech Separation
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Francis R. Bach, Michael I. Jordan
NIPS
1998
14 years 11 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
HICSS
2007
IEEE
98views Biometrics» more  HICSS 2007»
15 years 4 months ago
A Tool for Training and Assistance in Emergency Response Planning
This paper presents research on developing a new type of software tool for training and assisting the personnel in emergency response planning. The tool, called Disciple-VPT, will...
Gheorghe Tecuci, Mihai Boicu, Thomas Hajduk, Dorin...