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ICTAI
1994
IEEE
13 years 9 months ago
Iterative Strengthening: An Algorithm for Generating Anytime Optimal Plans
In order to perform adequately in real-world situations, a planning system must be able to nd the \best" solution while still supporting anytime behavior. We have developed ...
Randall J. Calistri-Yeh
CORR
2012
Springer
235views Education» more  CORR 2012»
12 years 21 days ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
IJCAI
2003
13 years 6 months ago
Automated Generation of Understandable Contingency Plans
Markov decision processes (MDPs) and contingency planning (CP) are two widely used approaches to planning under uncertainty. MDPs are attractive because the model is extremely gen...
Max Horstmann, Shlomo Zilberstein
AIPS
2010
13 years 7 months ago
Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement
Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become in...
Hootan Nakhost, Martin Müller 0003
CP
2000
Springer
13 years 9 months ago
Optimal Anytime Constrained Simulated Annealing for Constrained Global Optimization
Abstract. In this paper we propose an optimal anytime version of constrained simulated annealing (CSA) for solving constrained nonlinear programming problems (NLPs). One of the goa...
Benjamin W. Wah, Yixin Chen