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103
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ICTAI
2005
IEEE
15 years 6 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
165
Voted
INFOCOM
2011
IEEE
14 years 4 months ago
A high-throughput routing metric for reliable multicast in multi-rate wireless mesh networks
Abstract—We propose a routing metric for enabling highthroughput reliable multicast in multi-rate wireless mesh networks. This new multicast routing metric, called expected multi...
Xin Zhao, Jun Guo, Chun Tung Chou, Archan Misra, S...
121
Voted
ECAI
1998
Springer
15 years 5 months ago
Optimal Scheduling of Dynamic Progressive Processing
Progressive processing allows a system to satisfy a set of requests under time pressure by limiting the amount of processing allocated to each task based on a predefined hierarchic...
Abdel-Illah Mouaddib, Shlomo Zilberstein
105
Voted
ATAL
2006
Springer
15 years 4 months ago
Winning back the CUP for distributed POMDPs: planning over continuous belief spaces
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
Pradeep Varakantham, Ranjit Nair, Milind Tambe, Ma...
116
Voted
ICMLA
2009
14 years 10 months ago
Sensitivity Analysis of POMDP Value Functions
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...
Stéphane Ross, Masoumeh T. Izadi, Mark Merc...