An artificial intelligence perspective on autonomic computing policies

By Jeffrey O. Kephart, William E. Walsh. Proceedings. Fifth IEEE International Workshop on Policies for Distributed Systems and Networks, 2004. POLICY 2004., 2004

353 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/2e7a8021ab76fbc666d377896a28b8300d55081a

How researchers see this paper

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

In Artificial Intelligence

1. Julie Ann McCann
2. Markus C. Huebscher
3. Ladan Tahvildari
4. Mazeiar Salehie
5. Jeffrey O. Kephart
6. James E. Hanson
7. Ian Whalley
8. Steve R. White

In Computer Networks and Communications

1. Ladan Tahvildari
2. Julie Ann McCann
3. Markus C. Huebscher
4. Mazeiar Salehie
5. Jeffrey O. Kephart
6. James E. Hanson
7. Ian Whalley
8. Steve R. White

In Sociology and Political Science

1. Julie Ann McCann
2. Markus C. Huebscher

Citations in the corpus

• Self-adaptive software: Landscape and research challenges (2009, background): “In dynamic decision-making, policies [Kephart and Walsh 2004], rules [Liu et al.”
• A survey of autonomic computing—degrees, models, and applications (2008, methodology): “The goals are usually expressed using event-condition-action (ECA) policies, goal policies or utility function policies [Kephart and Walsh 2004].”
• An architectural approach to autonomic computing (2004, background): “An autonomic element should be able to translate requirements for its service characteristics (performance, etc.) into requirements for any services that it needs to request from other elements.”
• AI for Next Generation Computing: Emerging Trends and Future Directions (2022, neutral): “ML echniques, for example, can be used to discover patterns in the workload, where these patterns can be used to optimise resource anagement [14].”