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ICCAD
2002
IEEE
122views Hardware» more  ICCAD 2002»
15 years 10 months ago
Schedulability analysis of multiprocessor real-time applications with stochastic task execution times
This paper presents an approach to the analysis of task sets implemented on multiprocessor systems, when the task execution times are specified as generalized probability distrib...
Sorin Manolache, Petru Eles, Zebo Peng
ICML
1995
IEEE
16 years 2 months ago
Learning Policies for Partially Observable Environments: Scaling Up
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
Michael L. Littman, Anthony R. Cassandra, Leslie P...
ALT
2006
Springer
15 years 10 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama
ICTAI
2005
IEEE
15 years 7 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
AAAI
1996
15 years 3 months ago
Rewarding Behaviors
Markov decision processes (MDPs) are a very popular tool for decision theoretic planning (DTP), partly because of the welldeveloped, expressive theory that includes effective solu...
Fahiem Bacchus, Craig Boutilier, Adam J. Grove