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» Planning with predictive state representations
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ICMLA
2008
13 years 11 months ago
A Predictive Model for Imitation Learning in Partially Observable Environments
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
Abdeslam Boularias
JAIR
2006
179views more  JAIR 2006»
13 years 9 months ago
The Fast Downward Planning System
Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, ...
Malte Helmert
IJRR
2011
218views more  IJRR 2011»
13 years 4 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...
AIIA
2003
Springer
14 years 1 months ago
The Role of Different Solvers in Planning and Scheduling Integration
This paper attempts to analyze the issue of planning and scheduling integration from the point of view of information sharing. This concept is the basic bridging factor between the...
Federico Pecora, Amedeo Cesta
APIN
2004
81views more  APIN 2004»
13 years 9 months ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner