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IPPS
2006
IEEE
14 years 3 months ago
A framework to develop symbolic performance models of parallel applications
Performance and workload modeling has numerous uses at every stage of the high-end computing lifecycle: design, integration, procurement, installation and tuning. Despite the trem...
Sadaf R. Alam, Jeffrey S. Vetter
AAAI
1996
13 years 10 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
AAAI
1996
13 years 10 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
JCP
2008
139views more  JCP 2008»
13 years 9 months ago
Agent Learning in Relational Domains based on Logical MDPs with Negation
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Song Zhiwei, Chen Xiaoping, Cong Shuang
BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
13 years 6 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar