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UAI
2008
15 years 8 months ago
Hierarchical POMDP Controller Optimization by Likelihood Maximization
Planning can often be simplified by decomposing the task into smaller tasks arranged hierarchically. Charlin et al. [4] recently showed that the hierarchy discovery problem can be...
Marc Toussaint, Laurent Charlin, Pascal Poupart
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
15 years 8 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
AAAI
2004
15 years 8 months ago
A Multi-Resolution Pyramid for Outdoor Robot Terrain Perception
This paper addresses the problem of outdoor terrain modeling for the purposes of mobile robot navigation. We propose an approach in which a robot acquires a set of terrain models ...
Michael Montemerlo, Sebastian Thrun
AAAI
2006
15 years 8 months ago
Improving Approximate Value Iteration Using Memories and Predictive State Representations
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
Michael R. James, Ton Wessling, Nikos A. Vlassis
AAAI
2006
15 years 8 months ago
Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...