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Research in Knowledge Representation, Reasoning, and Acting

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Title: Research in Knowledge Representation, Reasoning, and Acting


1
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

2
Long-Term Goal
  • Theory and Implementation of
  • Natural-Language-Competent
  • Computerized Cognitive Agent/Robot
  • and Supporting Research in
  • Artificial Intelligence
  • Cognitive Science
  • Computational Linguistics.

3
Cassie
  • A computational cognitive agent
  • Embodied in hardware
  • or software-simulated
  • Based on SNePS and (M)GLAIR.

4
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
5
SNePS
  • SNePS is a
  • Logic-Based
  • Frame-Based
  • Network-Based
  • knowledge representation, reasoning, and acting
    system.

6
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

7
Some Recent CurrentResearch Projects
  • A General Characterization of Answers to
    Questions
  • KRR for Information Fusion for Cyber Security
  • Information Extraction for Soft Target
    Exploitation and Fusion
  • Ontological reasoning for GeoCLEF multilingual
    geographic information retrieval
  • Intermedia Performance Studio
  • Actor-agents in VR drama

8
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), in press.

9
KRR forInformation Fusionfor Cyber Security
  • Use SNePS to reason about computer networks, and
    about potential, and actual attacks.
  • Provide ontology-oriented SNePS GUI
  • A task of the National Center for Multisource
    Information Fusion
  • With Moises Sudit (IE CMIF) Michael Kandefer
    (CSE RA)
  • Funded by the Air Force Research Laboratory (AFRL)

10
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

11
Selecting a Predicatefor the Tree View
  • The user selects a predicate from the drop down
    menu, after which the tree is generated

12
Class Hierarchy
  • This view shows a small class hierarchy for hosts
    on a network

13
Part Of
  • This view shows a part of hierarchy.

14
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)

15
Information ExtractionforSoft Target
Exploitation and Fusion
  • Review relevant NLP tools.
  • Translate unstructured text messages to
    structured summaries.
  • E.g.
  • From
  • 03/17/07
  • Sabah Dulaimi arrived at 1035.
  • To
  • (m2 (date (m1 (day 17) (month 03) (year 07))))
  • (m3! (act arrive) (agent Sabah Dulaimi) (time
    1035))
  • With Shane Axtell (CL RA)
  • Funded by the US Army CERDEC (Communications-Elect
    ronics Research, Development and Engineering
    Center)

16
Ontological Reasoningfor GeoCLEF
  • Provide additional search terms to retrieve
    articles for queries such as
  • International sports competitions in the Ruhr
    area
  • and provide means of eliminating irrelevant
    answers.
  • With Miguel Ruiz (LIS), June Abbas (LIS), Thomas
    Bittner (PHI GEO), David Mark (GEO).

17
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/

18
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

19
The Trial The Trail
Bad guy agents hassling a human participant
20
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!
  • Register for CSE563 in Spring, 2007
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