This week we begin to talk about Connect, Which is how we connect the dots and make
sense of the world. How to go beyond learning to reasoning,
and why reasoning is needed, beyond simple learning as we have covered last week.
This leads us into logic. As well as its limits both fundamental as
well as those arising from the uncertain nature of the facts and rules that we
learn about the world so we will talk about reasoning under uncertainty in some
detail this week. And then, come full circle, back to
learning, where some of the techniques that we'll study, back to Bayes rule and
things like that again, will help us to learn better this time from text.
So here we go. To motivate why we might need to connect
the dots and go beyond mere learning and search, consider the following question.
Who is the leader of the USA? And consider asking this question of
search engine or any web intelligence system.
The system might be aware of some facts, such as x is the prime minister of some
country, c. X is the president of another country, c.
And many such facts for different values of x and c.
But, there is no such fact that X is the leader of the USA.
For example, we might have learned many such facts by looking at text and
extracting them, from textual documents, something that we'll come to, towards the
end of this week. But, for the moment assume that we do have
many such facts, but there is no such fact, for X being the leader of the USA.
Somehow we haven't learned this because we only learn the facts about specific posts
like president or prime minister so now what well if X is the president of C then
X is the leader of C. The system might know such facts or rules
which constitute its knowledge. As a result, combining of facts, such as
Obama is the President of the U.S.A., the system might be able to conclude that
Obama is the leader of the U.S.A. This is an example of reasoning.
Taking facts and knowledge which is rules and combining facts and knowledge to come
up with new facts. But reasoning can be pretty.
Manmohan Singh for example is the prime minister of India.
But Pranab Mukherjee is the President of India.
India has a prime minister as well as a president.
So who's the leader of India. You need more facts, and rules, to figure
this out. Much more knowledge is there for needed,
for example one might need to know that in India the president is a ceremonial post
whereas a prime minister is a leader. In other countries like France it is the
president who is leader. So knowledge is not necessarily static and
can lead to confusions if one doesn't understand the semantics of knowledge, so
reasoning is not as simple as it appears at first.
Lets take a look at a few more examples, to really understand how deep the problems
with reasoning can actually become. We've seen this example, a few weeks ago.
Book me an American flight to New York, as soon as possible.
Does the questioner or requester want a flight on American Airlines or on any
American carrier. It might depend on where that person is.
If he's in London any American carrier but if he's in New York or rather not in New
York but in, in Boston he might definitely mean the American Airlines flight.
This New Yorker, who fought at the Battle of Gettysburg, was once considered the
inventor of baseball. This is a question posed to the IBM
program Watson during the Jeopardy challenge of 2009.
There are two possible answers if you look at the web.
Alexander Cartwright, who wrote the rules of baseball.
Or Abner Doubleday. It turns out that its Abner Doubleday,
because this person actually fought at Gettysburg, and Watson got it right.
So Watson had to reason many different facts, including the fact that Abner
Doubleday also contributed to the rules of baseball, and in addition, fought at
Gettysburg. So these two things had to be put
together. Watson had to connect the dots, put two
and two together to make this conclusion and get this question right.
I think of a more difficult question like, who is the Tony of USA?
Those of you who are not from India. Tony is the cricket captain of India, so
this question is really asking a very deep question, in terms of, who is the
equivalent of the cricket captain of USA. Cricket is not really played in the US.
So what's the equivalent of cricket anywhere, baseball probably.
So, this is an example of, analogical reasoning.
So, x is to U.S.A., what cricket is to India, would give us baseball.
But, trouble is. There is no US baseball team.
So there, given that first step of reasoning doesn't seem to work, so one
needs to go beyond. Deductive reasoning to what is called
abductive reasoning. In the sense that one needs to find out
the best possible answer. Who is the most popular sportsman in the
USA? And there may be many popular sportsmen in
the USA, so one is trying to find the best possible answer from a probabilistic
perspective. This is an example of abductive reasoning,
as opposed to deductive reasoning, and we'll come across this later this week.
Furth, further this is an example of reasoning under uncertainty.
Most popular is not, given in any one web page or any one statement.
One needs to come to a conclusion based on a probabilistic assessment, of who appears
to be most popular, using some measures. So this is an example, uncertain reasoning
as well. The idea of adding reasoning to the web,
or web intelligence systems, is credited to Tim Berners-Lee who, if you remember,
is actually the, credited as being the inventor of the web in the first place way
back in the early'90's. In 2000, Tim Berners-Lee came out with his
vision for a semantic web, where instead of having.
Simple pages of text which could only be understood by human readers, one would
have. Linked to data on the web.
So it's not just text, but data which are facts.
Like, Obama is the President of the U.S.A., or.
President of U.S.A. Implies that someone is also the leader of
the U.S.A. And things like that.
So you'd have data which is linked to other data through inference rules as well
as engines or systems that could perform reasoning and therefore answer complicated
queries like, who is the Dhoni of U.S.A. or who is the leader of the U.S.A.?
We'll come back to the vision that Tim Berners-Lee, espoused in 2000 in a little
while. For the moment, lets take a closer look at
the concept of reasoning with a basic study of logic.
And how reasoning can be modeled formally. From there we'll go and study reasoning in
more detail. And finally, towards the end of this
week's lecture, we'll get back to how facts and rules required for reasoning can
be extracted from large volumes of text, such as are available on the web.