1 / 5

Architecture and Engineering of Self Aware Computer Systems

Explore the capabilities and knowledge bases needed to support self-aware computer systems. Learn about traces and explanations, including access to trace, abstraction of trace, and follow-up question capabilities. Discover the importance of ontologies and meta-information in providing explanations and informed information. Additionally, delve into the role of ontology and knowledge bases in self-aware computer systems.

michaelsarnold
Download Presentation

Architecture and Engineering of Self Aware Computer Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Architecture and Engineering of Self Aware Computer Systems Deborah McGuinness Stanford University

  2. Questions • What explanation capabilities should be supported by self-aware computer systems • What knowledge bases and ontologies are necessary to support self-aware computer systems

  3. Traces and Explanations • provide access to trace • provide abstraction of trace • may take trace as input • may use rewrite rules • provide follow-up question capabilities for more information • may use description of information manipulation (could be declarative representation of reasoning rules) • may use background domain ontologies with subject matter expertise • may use meta information (update date, authoritativeness, author, ….) • provide examples and counter examples • provide explanations for failures as well as success

  4. Explanations cont. • provide information informed by use of model of environment • may not include knowledge of other agents but physical information • provide information informed by use of model of other interacting agents • may use model of known recipient of explanation for presentation style, content, etc. • might include preferences, kb, reasoning strategies, context, what has been explained before • may be interruptible • may use description of plans, goals, known failures, intentions, beliefs, …. to present summary of current state, • provide information about alternatives • provide information about conflicting information • e.g., explanation of why x is red could offer an explanation of why x is not red if that is also deducible in the current state • may use language information (computer language e.g. OWL, presentation language (e.g., English, KIF, graph, …) • Make assumptions explicit • Explanations aimed at agents

  5. Ontologies and KBs • Upper level “general purpose” ontologies (SUMO, Cyc Upper Level, Dolce….) • Domain specific upper/mid levels (UNSPSC) • Domain specific upper/mid/&low levels (UMLS) • Domain specific KBs (large, current, authoritative.. Might consider CIA World Fact Book, crawled generated data, …) • Meta Information (dublin core properties, IW Registry, …) • Mental model ontologies

More Related