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AAAI
2006
14 years 11 months ago
Point-based Dynamic Programming for DEC-POMDPs
We introduce point-based dynamic programming (DP) for decentralized partially observable Markov decision processes (DEC-POMDPs), a new discrete DP algorithm for planning strategie...
Daniel Szer, François Charpillet
99
Voted
UAI
1998
14 years 11 months ago
Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
Ronald Parr
AIPS
2003
14 years 11 months ago
Synthesis of Hierarchical Finite-State Controllers for POMDPs
We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
Eric A. Hansen, Rong Zhou
ICRA
2006
IEEE
134views Robotics» more  ICRA 2006»
15 years 3 months ago
Hierarchical Map Building and Planning based on Graph Partitioning
— Mobile robot localization and navigation requires a map - the robot’s internal representation of the environment. A common problem is that path planning becomes very ineffic...
Zoran Zivkovic, Bram Bakker, Ben J. A. Kröse
76
Voted
FLAIRS
2001
14 years 11 months ago
Probabilistic Planning for Behavior-Based Robots
Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...
Amin Atrash, Sven Koenig