Research in
Knowledge 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
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
Body
KL (SNePS)
Independent
of lower-body
implementation
PMLa
PMLb
I/P s o c k e t s
Dependent
on lower-body
implementation
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!:
wff2!:
wff3!:
wff4!:
Inst({Albany,Syracuse,Rochester,Buffalo},City)
WestOf(Buffalo,Rochester)
WestOf(Rochester,Syracuse)
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 & Current
Projects
• 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 for
Information Fusion
in 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 Predicate
for 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)
– x[GreatLake(x) & Borders(x, NewYork)]
– x[GreatLake(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 Provost’s 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/sneps/
– Meets Tuesdays 10-12, 242 Bell Hall
– Join us!
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