Research in Knowledge Representation, Reasoning, and Acting

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Research inKnowledge Representation, Reasoning,
and Acting

• Stuart C. Shapiro
• Professor, CSE
• Affiliated Professor, Linguistics, Philosophy
• Director, Center for Cognitive Science
• Director, SNePS Research Group
• ACM Distinguished Scientist
• Fellow, AAAI
• Faculty Member
• Interdisciplinary MS in Computational
  Linguistics
• Center for MultiSource Information Fusion
• National Center for Ontological Research
• National Center for Geographic Information and
  Analysis

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Long-Term Goal

• Theory and Implementation of
• Natural-Language-Competent
• Computerized Cognitive Agent/Robot
• and Supporting Research in
• Artificial Intelligence
• Cognitive Science
• Computational Linguistics
• with application-oriented spinoffs.

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Cassie

• A computational cognitive agent
• Embodied in hardware
• or software-simulated
• Based on SNePS and (M)GLAIR.

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MGLAIR Agent Architecture
Mind
KL (SNePS)
Independent of lower-body implementation
Body
PMLa
PMLb
Dependent on lower-body implementation
I/P s o c k e t s
PMLc
Proprioception
Speech
W O R L D
Hearing
SAL
Vision
Motion
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SNePS

• SNePS is a
• Logic-Based
• Frame-Based
• Network-Based
• knowledge representation, reasoning, and acting
  system.

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Example Knowledge Base

• As logical assertions
• wff1! Inst(Albany,Syracuse,Rochester,Buffalo,
  City)
• wff2! WestOf(Buffalo,Rochester)
• wff3! WestOf(Rochester,Syracuse)
• wff4! WestOf(Syracuse,Albany)
• As frames
• (m1! (class City) (member Albany
  Syracuse Rochester Buffalo))
• (m2! (east Rochester) (west Buffalo))
• (m3! (east Syracuse) (west Rochester))
• (m4! (east Albany) (west Syracuse))

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Example KB as a Network
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Some Important SNePS Features

• First-person beliefs
• Not third-person truth about agent or world
• Beliefs are current beliefs
• Even if about the past
• On-line acting
• Reified propositions as well as acts
• Neither states nor times are privileged

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Some Recent CurrentProjects

• A General Characterization of Answers to
  Questions
• KRR for Information Fusion for Cyber Security
• Ontology Tool
• Logic of Arbitrary and Indefinite Objects
• Intermedia Performance Studio
• Actor-agents in VR drama

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A General Characterization of Answers to Questions

• Every clause descended from a query clause in
  resolution theorem proving is an answer to the
  query.
• General form of an answer
• H ? G ? Q
• H is Hypothetical component (optional)
• G is Generic component (optional)
• Q is Question component (either generic or
  specific)
• Example
• Cat(Boots), Tuna(x), Answer(Likes(Boots, x))
• Cat(Boots) ? ?x (Tuna(x) ? Likes (Boots, x))
• If Boots is a cat, then Boots likes to eat any
  tuna.
• D. T. Burhans S. C. Shapiro, Defining Answer
  Classes Using Resolution Refutation, Journal of
  Applied Logic 5,1 (March 2007), 70-91.

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KRR forInformation Fusionin the Cyber Security
Domain

• Use SNePS to reason about computer networks, and
  about potential, and actual attacks.
• A task of the National Center for Multisource
  Information Fusion
• With Moises Sudit (IE CMIF), Adam Stotz
  (CUBRC), Michael Kandefer (CSE RA)
• Funded by U.S. Air Force Research Laboratory,
  Rome, NY

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Added Java-SNePS API
SNePS GUI in development

• SNePS fuses information from
• SME domain rules
• Analyst background knowledge
• Ontology
• Network topology
• Common Vulnerabilities and Exposures
• INFERD attack tracks

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SNePS Ontology GUI

• SNePS GUI supports the loading and exporting of
  SNePS files in several formats.

• Allows the display of binary predicates as a tree
  hierarchy

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Hierarchical Relations

• Examples
• Subclass
• A dog is a mammal is a vertebrate.
• Part of
• A heart is part of a chest is part of a person.
• Reporting
• A professor reports to a chair reports to a dean.
• SNePS GUI finds hierarchical relations from the
  KB.

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Selecting a Predicatefor the Tree View

• The user selects a predicate from the drop down
  menu, after which the tree is generated

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Class Hierarchy

• This view shows a small class hierarchy for hosts
  on a network

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Part Of

• This view shows a part of hierarchy.

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Network View

• Shows the network representation (drawn using the
  JUNG network visualization tool) of a SNePS
  belief base
• User can zoom, move nodes, and save images as
  JIMI supported file types (jpg, bmp, png)
• Tooltips provide information about the
  propositions expressed by the nodes in the
  network
• Ex. This view shows assertions about the
  connectivity of various hosts (h0-h4)

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Logic of Arbitrary Indefinite Objects

• Instead of
• Borders(LakeErie, NewYork)
• ?xGreatLake(x) Borders(x, NewYork)
• ?xGreatLake(x) ? Borders(x, Ontario)
• Have
• Borders(LakeErie, NewYork)
• Borders(some x GreatLake(x), NewYork)
• Borders(any x GreatLake(x), Ontario)
• S. C. Shapiro, A Logic of Arbitrary and
  Indefinite Objects, KR2004, 565-575.

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Intermedia Performance Studio

• Buffalo-Region resource focusing on the
  integration of live actors, virtual avatars,
  intelligent actor-agents, dynamic sets and live,
  mobile audience members.
• With Sarah Bay-Cheng (THD DMS), Josephine
  Anstey (DMS), David Pape (DMS), Jon Bona (CSE
  RA)
• Funded by UB Provosts Interdisciplinary Research
  Development Fund (IRDF)
• See http//vrstudio.buffalo.edu/ips/wiki/

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The Trial The Trail

• Virtual Reality Drama with SNePS/GLAIR
  agent-actors.
• With Josephine Anstey (DMS), David Pape (DMS),
  and CSE grads Jon Bona, Albert Goldfain, Mike
  Kandefer, Vishwac Sena Kannan, Madhumitha
  Nagarajan

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The Trial The Trail
Bad guy agents hassling a human participant
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For More Information

• Shapiro http//www.cse.buffalo.edu/shapiro/
• SNePS Research Group http//www.cse.buffalo.edu/s
  neps/
• Meets Tuesdays 10-12, 242 Bell Hall
• Join us!