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Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility

Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility

Jeffrey Palmerino
Qi Yu
Travis J. Desell
Daniel E. Krutz
ArXiv (abs)PDFHTML

Papers citing "Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility"

4 / 4 papers shown
Title
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots
Pooyan Jamshidi
Javier Cámara
B. Schmerl
Christian Kastner
David Garlan
51
75
0
10 Mar 2019
Optimizing Long Short-Term Memory Recurrent Neural Networks Using Ant Colony Optimization to Predict Turbine Engine Vibration
Optimizing Long Short-Term Memory Recurrent Neural Networks Using Ant Colony Optimization to Predict Turbine Engine Vibration
A. ElSaid
Travis J. Desell
Fatima El Jamiy
James Higgins
Brandon Wild
AI4TS
35
130
0
10 Oct 2017
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks
Edward Choi
M. T. Bahadori
A. Schuetz
Walter F. Stewart
Jimeng Sun
151
1,103
0
18 Nov 2015
Self-Learning Cloud Controllers: Fuzzy Q-Learning for Knowledge Evolution
Self-Learning Cloud Controllers: Fuzzy Q-Learning for Knowledge Evolution
Pooyan Jamshidi
Amir Molzam Sharifloo
C. Pahl
Andreas Metzger
G. Estrada
37
73
0
02 Jul 2015

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