Knowledge Acquisition by an Intelligent Acting Agent

1
Knowledge Acquisition by an Intelligent Acting
Agent

• Michael Kandefer and Stuart Shapiro
• Department of Computer Science and Engineering,
  Center for Cognitive Science, and The National
  Center for Multisource Information Fusion
• mwk3shapiro_at_cse.buffalo.edu
• Logical Formalizations of Commonsense Reasoning
• AAAI 2007 Spring Symposia
• March 28, Stanford University, California

2
Outline

• Problem Description and Requirements
• Basic algorithm
• Example Interactions with Agent
• Architecture for agent embodiment (GLAIR)
• Symbol anchoring in GLAIR
• Solution Details
• Conclusions

3
McCarthys Second Telephone Problem

• McCarthy (1979) presents several problems that
  require commonsense reasoning.
• Second telephone problem
• A computer program that wants to telephone
  someone must reason about who knows the number.
  More generally, it must reason about what actions
  will obtain needed knowledge. Knowledge in books
  and computer files must be treated in a parallel
  way to knowledge held by persons. Furthermore,
  a program must often determine that it does not
  know something or that someone else doesnt.

McCarthy, J. 1979. First order theories of
individual concepts and propositions. In Hayes,
J. Michie, D. and Mikulich, L., eds.,
Machine Intelligence 9. Ellis Horwood Ltd.
129-147
4
Problem Requirements

• Determining the absence of the requisite
  knowledge for completing the task at hand.
• Determining the external information sources that
  might contain the required information.
• Knowing how to consult the source(s).
• Retrieving and representing the needed
  information.
• Completing the task with the acquired
  information.

5
External Sources

• Text files
• Telephone book
• John 305 Pine Tree Lane 479-2344
• Campus telephone directory
• Bill NSC 678 555-8989
• User is used as an external source
• User can type English statements asserting
  knowledge
• User can enter a phone number when queried by the
  agent

6
Basic Calling Procedure

• Believe none of the information sources have been
  searched
• If the individuals phone number is known, dial
  it.
• Otherwise, search each information source that is
  believed to contain the phone number, dial it if
  found.

7
Example Interactions

• What is Mikes telephone number?
• Mikes telephone number is 555-5612.
• Call Mike.
• I am pressing 5. I am pressing 5. I am pressing
  5. I am pressing 5. I am pressing 6. I am
  pressing 1. I am pressing 2.

8
Example Interactions

• What is Stus telephone number?
• I dont know.
• Call Stu.
• Checking Campus Database for Stus telephone
  number.
• I am pressing 5. I am pressing 5. I am pressing
  5. I am pressing 7. I am pressing 8. I am
  pressing 9. I am pressing 0.
• What is Stus telephone number?
• Stus telephone number is 555-7890.

9
Example Interactions

• What is Alberts telephone number?
• I dont know.
• Call Albert.
• Checking Phonebook for Alberts telephone
  number...
• I could not find Alberts phone number in any
  external information
• source available to me.
• Do you know Alberts number? Yes
• What is Alberts number (e.g. 555-5555)?
  555-1234
• I am pressing 5. I am pressing 5. I am pressing
  5. I am pressing 1. I am pressing 2. I am
  pressing 3. I am pressing 4.
• What is Alberts telephone number?
• Alberts telephone number is 555-1234.

10
GLAIR

• Grounded Layered Architecture with Integrated
  Reasoning
• Architecture for embodied agents.
• Knowledge layer (KL)
• Conscious reasoning
• Beliefs, Plans and Policies
• Perceptuo-motor layer (PML)
• Primitive actions
• Link to embodiment
• Sensory-actuator layer (SAL)
• Sensors and actuators

KL
PML
SAL
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Implementing the KL

• SNePS-based agents have first-person belief base
• Structured as a set of propositions in a
  language of thought independent of the natural
  language used to express these beliefs
• SNePSLOG higher-order logical language
  interface to SNePS

12
GLAIR and Symbol Anchoring
KL
PML
SAL
SNePSLOG terms
Mikelex
Lexicon (Mikelex ((ctgy
. npr) (root . Mike")))
English
Mike
SNePSLOG expressions Has(b5,compCat(lex(teleph
onelex), lex(numberlex)), b10). Name(b5,
Mikelex). Value(b10,N(n5,N(n5,N(n5,N(n5,
N(n6,N(n1,n2))))))).
Grammar GATN
English Mikes telephone
number is 555-5612.
SNePSLOG prim. act terms
act(lex(presslex), n5)
Attach-primaction (attach-primaction
lex(presslex) press) (press 5)
Sensors and actuators I am
pressing 5. Presses button 5 on
simulated phone
13
Domain of Discourse

• Entities
• Propositions
• Acts
• Policies
• Things

14
Individual Constants Denoting Things

• Mikelex - Lexeme Mike
• telephonelex - Lexeme telephone
• numberlex - Lexeme number
• studentlex - Lexeme student
• professorlex - Lexeme professor
• digitlex - Lexeme digit
• sequencelex - Lexeme sequence
• presslex Lexeme press
• bDB - A campus telephone directory
• bPB - A telephone directory
• n0-n9 - Digits 0-9
• b5 denotes the individual named Mike
• b10 denotes the value of Mikes telephone
  number.

15
Thing-denoting Functions

• lex(x) the thing that can be expressed by the
  lexeme denoted by x
• compCat(c1,c2) the complex category which is
  a subcategory of the category denoted by
  c2 and is modified by c1
• Ex. compCat(lex(telephonelex),lex(numberlex))

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Telephone Number Values

• N(d,n) - the sequence d,n
• N(n5,N(n5,N(n5,N(n1,N(n2,N(n3,n4)))))
• Digit sequence axiomall(d)(Member(d,
  lex(digitlex)) gt all(n)(Member(n,lex(digitle
  x)),
  Member(n,compCat(lex(digitlex),le
  x(sequencelex))) vgt Member(N(d,n),
  
  compCat(lex(digitlex),lex(sequencelex))))).

17
Proposition-valued Functions

• Possession
• Has(p,r,o) ps r is o.
• Name(e,pn) the proper-name of entity e is pn.
• Value(e,v) - the value of entity e is v.
• Ex. Has(b5,compCat(lex(telephonelex),lex(numberl
  ex)), b10).
• Name(b5, Mikelex).
• Value(b10, N(n5,N(n5,N(n5,N(n5,N(n6,N
  (n1,n2))))))).
• Act definition
• ActPlan(a1,a2) To perform act a1, perform act a2.

18
Act-denoting Functions (SNeRE)

• SNeRE acting system used for an online acting
  solution
• SNeRE primitive acts
• snsequence(a1,a2)
• snif(if(p1,a),...,if(pn,an),else(da))
• withsome(x, p(x), a(x), da)
• SNeRE Mental Acts
• disbelieve(p)
• believe(p)

19
Primitive Act-denoting Functions

• Information retrieving primitives
• search(p, s)
• ask-user(p)
• Dialing Primitives
• pickup()
• putdown()
• press(n)

20
Symbol Anchoring vs. Quotation

• Since
• propositions are first-class objects in the
  domain,
• proposition-denoting functional terms are
  employed
• alignment is used to connect lexeme-denoting
  terms with the actual lexemes
• Therefore, there is no need for a quotation or
  string operator.

21
Belief Base Introspection

• Agent requires the ability to introspect on its
  belief base and act on the results
• Lack of knowledge reasoning is captured by the
  else clause of withsome
• Ex. withsome(n,n1,
• (Has(b5,compCat(lex(telephonelex),
  lex(numberlex)),n1) and Value(n1,n)),
• dial(b5,n),
• lookup(b5))

22
Reasoning About External Information Sources

• Determining the source
• all(p)(Member(p, lex(personlex))
• gt (Member(p,lex(professorlex)),
  Member(p,lex(studentlex))
• vgt Contains(bDB,compCat(lex(tel
  ephonelex),lex(numberlex)),p))).
• all(p)(Member(p, lex(personlex)) gt
  (Member(p,lex(professorlex)),
  Member(p,lex(studentlex)) gt
  Contains(bPB,compCat(lex(telephonelex),lex(numberl
  ex)),p))).
• Using the source
• withsome(i,
• (Member(i,compCat(lex(informationlex),lex(source
  lex)))
• and Contains(i,compCat(lex(telephonelex),lex(num
  berlex)),p)
• and Searched(i)),
• )

23
Using the Information

• Regardless of how the information is acquired the
  dial defined act is performed
• dial is a recursive procedure that processes the
  digit sequence one digit at a time, performing
  press on each.

24
Dial Defined Act

• all(a,v,pn)(Member(a,lex(personlex)),
• Value(v,pn),
• Has(a,compCat(lex(telephonelex),
  lex(numberlex)), v)
• gt ActPlan(dial(a,pn),
  ordered-press(pn))).
• all(n1,n2)(Member(N(n1,n2), compCat(lex(digitlex),
  lex(sequencelex)))
• gt ActPlan(ordered-press(N(n1,n2
  )),
• snif(if(Member(n2,lex(digitlex)),
• snsequence(act(lex(pressl
  ex),n1),
  act(lex(presslex),n2))),
• else(snsequence(act(lex(pressle
  x),n1), ordered-press(n2)))))).

25
Conclusions

• Demonstrated the necessary elements to an
  embodied solution to McCarthys Second Telephone
  number using SNePS
• Determining missing information with withsome
• Determining external sources to check using rules
• Consulting those sources through the GLAIR
  architecture
• Used GLAIR to retrieve and represent the needed
  information by anchoring the symbols of the
  knowledge base with the English language
• Executed the task using the SNePS acting system
  with integrated reasoning