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JAIR
2010
115views more  JAIR 2010»
13 years 5 months ago
An Investigation into Mathematical Programming for Finite Horizon Decentralized POMDPs
Decentralized planning in uncertain environments is a complex task generally dealt with by using a decision-theoretic approach, mainly through the framework of Decentralized Parti...
Raghav Aras, Alain Dutech
AUTOMATICA
2007
124views more  AUTOMATICA 2007»
13 years 7 months ago
Motion planning in uncertain environments with vision-like sensors
In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
Suman Chakravorty, John L. Junkins
ATAL
2006
Springer
13 years 11 months ago
Solving POMDPs using quadratically constrained linear programs
Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
CCE
2004
13 years 7 months ago
Dynamic programming in a heuristically confined state space: a stochastic resource-constrained project scheduling application
The Resource-Constrained Project Scheduling Problem(RCPSP) is a significant challenge in highly regulated industries, such as pharmaceuticals and agrochemicals, where a large numb...
Jaein Choi, Matthew J. Realff, Jay H. Lee
NIPS
1998
13 years 8 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch