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AIPS
2008
13 years 10 months ago
An Online Learning Method for Improving Over-Subscription Planning
Despite the recent resurgence of interest in learning methods for planning, most such efforts are still focused exclusively on classical planning problems. In this work, we invest...
Sung Wook Yoon, J. Benton, Subbarao Kambhampati
AIPS
2008
13 years 10 months ago
Efficient ADD Operations for Point-Based Algorithms
During the past few years, point-based POMDP solvers have gradually scaled up to handle medium sized domains through better selection of the set of points and efficient backup met...
Guy Shani, Pascal Poupart, Ronen I. Brafman, Solom...
AIPS
2008
13 years 10 months ago
What Makes Planners Predictable?
In recent work we showed that models constructed from planner performance data over a large suite of benchmark problems are surprisingly accurate; 91-99% accuracy for success and ...
Mark Roberts, Adele E. Howe, Brandon Wilson, Marie...
AIPS
2008
13 years 10 months ago
Multi-Objective Evolutionary Algorithms for Scheduling the James Webb Space Telescope
Effective scheduling of the James Webb Space Telescope (JWST) requires managing the trade-off between multiple scheduling criteria including minimizing unscheduled time, angular m...
Mark E. Giuliano, Mark D. Johnston
AIPS
2008
13 years 10 months ago
Multiagent Planning Under Uncertainty with Stochastic Communication Delays
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...