{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81696"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81696","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"POLUS: A Self -Evolving Model-Based Approach for Automating the Observe -Analyze -Act Loop","abstract":"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.).","abstract_html":"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. 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