1. Inference Web: Portable and Sharable Proofs for Hybrid Systems Deborah L. McGuinness, Paulo Pinheiro da Silva and Bill MacCartney with Richard Fikes, Gleb Frank, Jessica Jenkins, Rob McCool, Yulin Li Knowledge Systems Laboratory Stanford University http://www.ksl.stanford.edu {dlm | pp} @ksl.stanford.edu

2. McGuinness, Pinheiro da Silva, and MacCartney, 20032 Motivation - TRUST If users (humans and agents) are to use and integrate system answers, they must trust them. System transparency supports understanding and trust. Thus, systems should be able to explain their actions, sources, and beliefs. Also, if systems are hybrid, it is useful to work in an integrated yet separable manner.

3. McGuinness, Pinheiro da Silva, and MacCartney, 20033 Technical Infrastructure Reqs n Provenance information - explain where source information: source name, date and author of last update, author(s) of original information, trustworthiness rating, etc. n Reasoning information - explain where derived information came from: the reasoner used, reasoning method, inference rules, assumptions, etc. n Explanation generation – provide abbreviated descriptions of the proof – may include reliance on a description of the representation language (e.g., DAML+OIL, OWL, RDF, …), axioms capturing the semantics, rewriting rules based on axioms, other abstraction techniques, etc. n Distributed web-based deployment of proofs - build proofs that are portable, sharable, and combinable that may be published on multiple clients, registry is web available and potentially distributed, … n Proof/explanation presentation - Presentation should have manageable (small) portions that are meaningful alone (without the context of an entire proof), users should be supported in asking for explanations and follow-up questions, users should get automatic and customized proof pruning, web browsing option, multiple formats, customizable, etc.

4. McGuinness, Pinheiro da Silva, and MacCartney, 20034 Inference Web Framework for explaining reasoning tasks by storing, exchanging, combining, annotating, filtering, segmenting, comparing, and rendering proofs and proof fragments provided by reasoners. l DAML+OIL/OWL specification of proofs is an interlingua for proof interchange l Proof browser for displaying IW proofs and their explanations (possibly from multiple inference engines) l Registration for inference engines/rules/languages l Proof explainer for abstracting proofs into more understandable formats l Proof generation service for facilitate the creation of IW proofs by inference engines l Prototype implementation with Stanford’s JTP reasoner and SRI’s SNARK reasoner l Discussions with Boeing, Cycorp, Fetch, ISI, Northwestern, SRI, UT, UW, W3C, …

5. McGuinness, Pinheiro da Silva, and MacCartney, 20035 IW Browsers Registrars World Wide Web Registry entries Inference Web Architecture proof fragments non-IW documents Web agent Web document URL reference Agent dependency Caption Document maintenance Inference engines Reasoner agent

6. McGuinness, Pinheiro da Silva, and MacCartney, 20036 IW Registry and Registrar n IW Registry has meta-data useful for disclosing data provenance and reasoning information such as descriptions of l inference engines along with their supported inference rules l Information sources such as organizations, publications and ontologies l Languages along with their axioms n The Registry is managed by the IW Registrar

7. McGuinness, Pinheiro da Silva, and MacCartney, 20037 Inference Engine Registration (1) n An entry for SRI’s SNARK engine n An entry for SNARK’s Binary Resolution inference rule n Engine registration involves the creation of an engine entry and its association with entries of inference rules n Rule entries can be either reused or added to the registry

8. McGuinness, Pinheiro da Silva, and MacCartney, 20038 Inference Engine Registration (2) n Otter’s binary resolution, hyper-resolution and paramodulation rules were reused for the registration of SNARK n Assumption and negated conclusion rules were added for SNARK Rule reuse addition

9. McGuinness, Pinheiro da Silva, and MacCartney, 20039 Inference Engine Registration (3) Summarizing the Inference Engine Registration process: n Use the registry to include meta-information about the engine and its rules l Add an entry for the new inference engine l Identify the core inference rules supported by the engine l Add unregistered core inference rules, if any l Associated the core rules with the core inference engine n Prepare the engine to dump proofs in the IW format l Implement a routine for calling the proof generator service u Example routines in Java and Lisp can be provided l Publish successful results of the proof generator services in portable proof format (OWL/DAML/RDF/XML compliant files) n Browse your proofs in the IW Browser

10. McGuinness, Pinheiro da Silva, and MacCartney, 200310 Generation of IW proofs Reasoner Proof fragments Registry Registrar WWW Proof generator service (1) Send node information: reasoner ID, labeling sentence in KIF, rule ID, antecedent URIs, bindings, and sourceID (2) Verify information (3) Return proof fragments (4) publish proof fragments (can collect statistics, provide feedback,…)

11. McGuinness, Pinheiro da Silva, and MacCartney, 200311 Integration with SNARK n Done by non-SNARK author to test strategies for integration n Tests alternative reasoning strategy – proof by contradiction n No special modifications made as a test of leverage n Learned some new requirements (CNF processing, reasoning modes may be useful, …) n Initial integration fairly easy n More complete integration in process

12. McGuinness, Pinheiro da Silva, and MacCartney, 200312 SNARK Example: nuclear threats (1)ore  refiner  material (2)black-mkt  material (3)black-mkt   ore (4)  black-mkt  ore (5)material  detonator  casing  warhead (6)  material   warhead (7)  detonator   warhead (8)  casing   warhead (9)warhead  missile  nuke (10)warhead  truck  nuke (11)missile  truck “Weapons-grade nuclear material may be derived from uranium ore if refining technology is available, or it may be acquired from a black market source. Foobarstan is known to have either uranium ore or a black market source, but not both. Foobarstan will build a nuclear warhead if and only if it can obtain nuclear material, a detonator, and the bomb casing. A warhead and a missile, or a warhead and a truck, constitute a nuclear threat. Foobarstan has either a missile or a truck.” QUESTION: Is Foobarstan a nuclear threat?

13. McGuinness, Pinheiro da Silva, and MacCartney, 200313 Example: proof by contradiction

14. McGuinness, Pinheiro da Silva, and MacCartney, 200314 Example: a proof tree

15. McGuinness, Pinheiro da Silva, and MacCartney, 200315 An example in FOL

16. McGuinness, Pinheiro da Silva, and MacCartney, 200316 Registering SNARK: next steps n Add support for ‘source’ and ‘author’ fields l Match with IW-registered ontologies where possible n Standardize treatment of SNARK rewrites l When do rewrites correspond to resolution, hyperresolution, paramodulation? l Utilize SNARK rewrites for IW abstraction strategies l Consider tableaux approaches for explanation n Implement correct handling of SNARK procedural attachments l SNARK includes procedural attachments for math, lists l User can define new procedural attachments on the fly l This constitutes an inference rule with an open-ended definition n Track variable bindings through course of proof n Integrate IW interface into SNARK standard release

17. McGuinness, Pinheiro da Silva, and MacCartney, 200317 Conclusion/Next Steps n Proof specification ready for feedback/use http://www.ksl.stanford.edu/software/iw/ n Proof browser prototype operational and expanding l Recent: ground axiom collection, source doc/ontology collection, aggregation view l Current: multiple formats, simplification, pruning, …) n Registration service expansion - integration with XML database, use in EPCA, registration of services (with Fetch) n Inference engine integration work – further rewrites for JTP (temporal reasoner), SNARK, begin with KM – explanation style for HALO. n Integration with web services – current: KSL Wine Agent, KSL DQL client (NIMD implementation), begin with registration of web services (Fetch) n Documentation – more examples, etc. More comments solicited (thanks to date to some for comments including Berners-Lee, Chalupsky, Chaudhri, Clark, Connolly, Forbus, Hawke, Hayes, Lenat, Murray, Porter, Reed, Waldinger, …)

18. McGuinness, Pinheiro da Silva, and MacCartney, 200318 Extra

19. McGuinness, Pinheiro da Silva, and MacCartney, 200319 Proof browsing: an example (1) n Tools can be used for browsing IW proofs. The following example demonstrates the use of the IW Browser to visualize, navigate and ask follow-up questions. n Lets assume a Wines ontology: n Determination of the type of a concept or instance is a typical problem on the Semantic Web. A reasoner may ask either about the type of an object and may also ask if an object is of a particular type Example Query : (rdf:type TonysSoftShell ?X) Example DAML KB : <rdf:RDF xmlns:rdf =“http://www.w3.org/1999/02/22-rdf-syntax-ns#” xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#">

20. McGuinness, Pinheiro da Silva, and MacCartney, 200320 Proof browsing: An example (2) n Browsers can display portions of proofs. n Selecting premises users can navigate throughout proof trees. Proof browsing: An example (2)

21. McGuinness, Pinheiro da Silva, and MacCartney, 200321 Trust Disclosure n IW proofs can be used: l to provide provenance for “lookup” information l to display (distributed) deduction justifications l to display inference rule static information Trust Disclosure

22. McGuinness, Pinheiro da Silva, and MacCartney, 200322 Technical Requirements n annotate information with meta information such as source, date, author, … at appropriate granularity level (per KB, per term, …) n explain where source information is from n explain where derived information came from n prune information and explanations for presentation (utilizing user context and information context for presentation) n provide a query language capable of expressing user requests along with filtering restrictions n provide a ubiquitous source annotation language n provide a ubiquitous proof language for interchange n Compare answers n propagate meta information appropriately (if I got something from a source I consider trusted and you consider me a trusted source, you may want to consider my source trusted as well) n Identify multiple (or unknown) truth values