On the use of hybrid reinforcement learning for autonomic resource allocation

By G. Tesauro, Nicholas K. Jong, Rajarshi Das, Mohamed N. Bennani. 2007

127 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Stéphane Ross
2. Prakash Panangaden
3. Gheorghe Comanici
4. Jim Duggan
5. Enda Barrett
6. Enda Howley
7. Shie Mannor
8. Assaf Hallak

In Information Systems

1. Stéphane Ross
2. Mahdi Milani Fard
3. Shie Mannor
4. Assaf Hallak

Citations in the corpus

• Reinforcement learning (2019, neutral): “Information is passed from the environment or the world to the agent in the form of observations .”
• Applying reinforcement learning towards automating resource allocation and application scalability in the cloud (2013, methodology): “Tesauro investigated the use of a hybrid reinforcement learning technique for autonomic resource allocation [8].”
• Adaptive Control of Epileptic Seizures using Reinforcement Learning (2010, background): “On a real-world application of RL for autonomic resource allocation, the adoption of function approximators that generalize across action is justified by a reduction in the number of exploratory samples needed to learn a good policy [69].”