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» Efficient Algorithms for Online Decision Problems
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ICTAI
2005
IEEE
14 years 3 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze
ICRA
2010
IEEE
136views Robotics» more  ICRA 2010»
13 years 8 months ago
Efficient planning under uncertainty for a target-tracking micro-aerial vehicle
A helicopter agent has to plan trajectories to track multiple ground targets from the air. The agent has partial information of each target's pose, and must reason about its u...
Ruijie He, Abraham Bachrach, Nicholas Roy
AIPS
2007
14 years 16 days ago
A Fast Incremental Algorithm for Maintaining Dispatchability of Partially Controllable Plans
Autonomous systems operating in real-world environments must be able to plan, schedule, and execute missions while robustly adapting to uncertainty and disturbances. Previous work...
Julie A. Shah, John Stedl, Brian C. Williams, Paul...
JAMDS
2000
90views more  JAMDS 2000»
13 years 10 months ago
Stratified filtered sampling in stochastic optimization
We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distri...
Robert Rush, John M. Mulvey, John E. Mitchell, Tho...
MANSCI
2007
139views more  MANSCI 2007»
13 years 10 months ago
A Market-Based Optimization Algorithm for Distributed Systems
In this paper, a market-based decomposition method for decomposable linear systems is developed. The solution process iterates between a master problem that solves the market-matc...
Zhiling Guo, Gary J. Koehler, Andrew B. Whinston