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IJRR
2011
218views more  IJRR 2011»
13 years 3 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...
ANTSW
2006
Springer
14 years 18 days ago
An Estimation of Distribution Particle Swarm Optimization Algorithm
Abstract. In this paper we present an estimation of distribution particle swarm optimization algorithm that borrows ideas from recent developments in ant colony optimization. In th...
Mudassar Iqbal, Marco Antonio Montes de Oca
IJRR
2010
132views more  IJRR 2010»
13 years 6 months ago
LQR-trees: Feedback Motion Planning via Sums-of-Squares Verification
Advances in the direct computation of Lyapunov functions using convex optimization make it possible to efficiently evaluate regions of attraction for smooth nonlinear systems. Her...
Russ Tedrake, Ian R. Manchester, Mark Tobenkin, Jo...
AIPS
2006
13 years 10 months ago
Planning with Temporally Extended Goals Using Heuristic Search
Temporally extended goals (TEGs) refer to properties that must hold over intermediate and/or final states of a plan. Current planners for TEGs prune the search space during planni...
Jorge A. Baier, Sheila A. McIlraith
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 10 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu