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IROS
2009
IEEE
163views Robotics» more  IROS 2009»
14 years 2 months ago
On the performance of random linear projections for sampling-based motion planning
— Sampling-based motion planners are often used to solve very high-dimensional planning problems. Many recent algorithms use projections of the state space to estimate properties...
Ioan Alexandru Sucan, Lydia E. Kavraki
EMO
2001
Springer
107views Optimization» more  EMO 2001»
14 years 13 days ago
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...
Joshua D. Knowles, Richard A. Watson, David Corne
ICDM
2008
IEEE
106views Data Mining» more  ICDM 2008»
14 years 2 months ago
Boosting Relational Sequence Alignments
The task of aligning sequences arises in many applications. Classical dynamic programming approaches require the explicit state enumeration in the reward model. This is often impr...
Andreas Karwath, Kristian Kersting, Niels Landwehr
PUK
2000
13 years 9 months ago
Heuristic Search Planning with BDDs
Abstract. In this paper we study traditional and enhanced BDDbased exploration procedures capable of handling large planning problems. On the one hand, reachability analysis and mo...
Stefan Edelkamp
CDC
2009
IEEE
147views Control Systems» more  CDC 2009»
13 years 5 months ago
A probabilistic approach for control of a stochastic system from LTL specifications
We consider the problem of controlling a continuous-time linear stochastic system from a specification given as a Linear Temporal Logic (LTL) formula over a set of linear predicate...
Morteza Lahijanian, Sean B. Andersson, Calin Belta