POLUS: A Self -Evolving Model-Based Approach for Automating the Observe -Analyze -Act Loop

The details of the POLUS methodology consist of: Representation of domain-specific details as models; creation and evolution of these models in an automated fashion; decision-making for the corrective action(s) to be invoked at run-time; handling divergent system behavior during action execution. POLUS is the first-of-a-kind in using a model-based approach for OAA automation; by applying the following operational principles. P OLUS addresses challenges related to model inaccuracies in real-world systems, and the computational complexity of decision-making: (1) Models don't need to be perfectly accurate---they only need to be accurate enough to maintain the relative ordering during action selection; (2) The objective of action selection is not to find the most optimal one, but rather to avoid the worst ones; (3) Creation of models is not a one-time activity---it is a continuous process over the lifetime of the system. (Abstract shortened by UMI.).

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Uttamchandani, Sandeep

Contributors dc:contributor

• Agha, Gul A.

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI3199160

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81696