Common Sense and Artificial Intelligence

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Common Sense and Artificial Intelligence

• Pradyumna Kumar ReddyJayanth Tadinada
• Prithvi Raj KanakamSatish Kumar
  GugulothDevashish Sethia

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It is way past 2001 Where the hell is HAL?
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The Goals of Artificial Intelligence

• The need to reconsider the goals of AI
• Mental Amplification
• Thanks to engineering, we can travel faster and
  farther than our muscles can take us, see things
  we cant otherwise see, talk louder than our
  lungs can shout.

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Expert Systems

• Our system Some diagnosis expert system like
  MYCIN
• The Patient An old rusted car in the back yard
• Question Answer session with the expert system
• Are there spots on the body? YES
• Are there more spots on the trunk than anywhere
  else? YES
• What color are the spots? REDDISH BROWN
• Diagnosis The car has measles
• Degree of confidence HIGH

Example taken from Google Techtalk by Doug Lenat,
may 2006
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Expert Systems (cont.)

• Our system An intelligent car loan approval
  system
• Question Answer session with the expert system
• Date of Birth 1989
• Time spent at current job 19 YEARS
• Result Loan approved

Example taken from Google Techtalk by Doug Lenat,
May 2006
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Expert Systems (cont.)

• So why do the expert systems have this
  problem?
• Because they dont have common sense
• The expert systems only know equations and
  variables.

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Search

• Is the Eiffel tower taller than the Taj Mahal?
• Cannot combine knowledge it already has access
  to.
• Why cant the search engine do the simple math
  and give us the answer
• Lack of common sense

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Natural Language Processing

• The police watched demonstrators...
  because they feared violence. because they
  advocated violence.
• Mary and Sue are sisters.Mary and Sue are
  mothers.
• George Burns My aunt is in the hospital, I went
  to see her today, and took her flowers.Gracie
  Allen George, Thats terrible! You should have
  brought her flowers.

Example taken from Google Techtalk by Doug Lenat,
may 2006
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ASSUME OUR COMPUTER NOW HAS Common Sense
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Search
Query someone smiling Caption A
mother helping her child take her first step
When you are happy, you smile You become happy
when someone you love accomplishes a
milestone Taking ones first step is a
milestone Parents love their children
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Search

• Query Government buildings damaged in
  terrorist events in Beirut between 1990 and
  2001.
• Document 1993 pipe bombing of Frances embassy
  in Lebanon

Beirut is in Lebanon Embassies are govt.
buildings 1993 is in the 1990s If there was a
pipe bombing, then it is mostly a terrorist
attack and not an accident etc.
Example taken from Google Techtalk by Doug Lenat,
may 2006
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Natural Language Processing

• The police watched demonstrators...
  because they feared violence. because they
  advocated violence.
• Mary and Sue are sisters.Mary and Sue are
  mothers.
• George Burns My aunt is in the hospital, I went
  to see her today, and took her flowers.Gracie
  Allen George, Thats terrible! You should have
  brought her flowers.

Example taken from Google Techtalk by Doug Lenat,
may 2006
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So How do we implement Common Sense?
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What is this Knowledge?

• Millions of facts, rules of thumb etc.
• Represented as sentences in some language.
• If the language is Logic, then computers can do
  deductive reasoning automatically.
• This representation of a set of concepts within
  a domain and the relationships between those
  concepts is called Ontology
• The sentences are expressed in formal logic
  notation.
• The words and the logic sentences about them
  are called Formal Ontology

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Hierarchy in Ontology
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Predicate Calculus Representation
Parents love their children This can be
represented as (ForAll ?P (ForAll ?C
(implies (and (isa ?P Person)
(child ?P ?C)) (loves ?P ?C))))) For all P,
For all C, P is a person AND C is a child of P
implies P loves C
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Reasoning Using Logic
Examples Simple (isa Socrates Man) (ForAll
?x (implies (isa ?x Man) (isa ?x Mortal))) (isa
Socrates Mortal) gtYes Harder Using general
and specific knowledge Can a can can-can? gt No
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Cyc

• Cyc is an AI project that attempts to assemble a
  comprehensive ontology and knowledge of everyday
  common sense knowledge.
• Its goal is to enable AI applications to perform
  human like reasoning.
• The project was started by CYcorp, a Texas based
  company.
• All the aforementioned features were
  incorporated in Cyc.

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Cyc

• Cyc has a huge knowledge base which it uses for
  reasoning.
• Contains
• 15,000 predicates
• 300,000 concepts
• 3,200,000 assertions
• All these predicates, concepts and assertions
  are arranged in numerous ontologies.

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Cyc Features

• Uncertain Results
• Query who had the motive for the assassination
  of Rafik Hariri?
• Since the case is still an unsolved political
  mystery, there is no way we can ever get the
  answer.
• In cases like these Cyc returns the various view
  points, quoting the sources from which it built
  its inferences.
• For the above query, it gives two view points
• USA and Israel as quoted from a editorial in
  Al Jazeera
• Syria as quoted from a news report from CNN

Example taken from Google Techtalk by Doug Lenat,
may 2006
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Cyc Features (cont.)

• It uses Google as the search engine in the
  background.
• It filters results according to the context of
  the query.
• For example, if we search for assassination of
  Rafik Hariri, then it omits results which have a
  time stamp before that of the assassination date.

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Cyc Features (cont.)

• Qualitative Queries
• Query Was Bill Clinton a good President of the
  United States?
• In cases like these, Cyc returns the results in
  a pros and cons type and leave it to the user to
  make a conclusion.
• Queries With No Answer
• Query At this instance of time, Is Alice
  inhaling or Exhaling?
• The Cyc system is intelligent enough to figure
  out queries which can never be answered correctly.

Example taken from Google Techtalk by Doug Lenat,
may 2006
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The Dream

• The ultimate goal is to build enough common
  sense into the Cyc system such that it can
  understand Natural Language.
• Once it understands Natural Language, all the
  system has to do is crawl through all the online
  material and learn new common sense rules and
  evolve.
• This two step process of building common sense
  and using machine learning techniques to learn
  new things will make the Cyc system an infinite
  source of knowledge.

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Drawbacks

• There is no single Ontology that works in all
  cases.
• Although Cyc is able to simulate common sense it
  cannot distinguish between facts and fiction.
• In Natural Language Processing there is no way
  the Cyc system can figure out if a particular
  word is used in the normal sense or in the
  sarcastic sense.
• Adding knowledge is a very tedious process.

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References

1. Marvin Minsky, Why People Think Computers Cant,
   AI Magazine, vol. 3 no. 4, Fall 1982.
2. Douglas B Lenat, Keynote address computers vs
   common sense, Proceedings of the 1991 ACM SIGMOD
   international conference on Management of data,
   April 1991.
3. Douglas B Lenat, R V Guha, Karen Pittman, Dexter
   Pratt and Mary Shepherd, Cyc toward programs
   with common sense, Communications of the ACM,
   1990.
4. Douglas B Lenat, George Miller and Toshio Yokoi,
   CYC, WordNet, and EDR critiques and responses,
   Communications of the ACM, 1995.
5. Talk by Douglas Lenat, Google techtalks, May 2006