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Chat Bots
Ruta Mehta
Mugdha Jain
Jeetendra MirchandaniWelcome to the world of living people and artificial intelligence entities called bots!
Questions We’ll Answer
What is it? Who wants it? Why? Since when is it around? How does it work? How do you test it? Can it answer all my questions? Can I make one of my own? Where can I put it to work?
A Chat Bot…
Introduction
Chat Bot: A computer program that can talk to humans in natural language!
Uses Artificial Intelligence Markup Language (AIML) to represent knowledge.
Can replace a human for monotonous jobs of answering queries, e.g. E-help desk.
How It All Started
Eliza – the first chat bot made by Joseph Weizenbaum. Eliza Effect
– tendency of humans to attach associations to terms from prior experience.
Working of Eliza is based on – Knowledge Representation – Pattern Recognition – Substitution of key words into known phrases.
How does it respond
Looks for certain patterns of words in the user's input. Replies with pre-determined output, if the pattern is
matched. Needs to have an idea of what the user will chat Has suitable responses defined in the AIML file
Knowledge Representation
Types of AIML objects– Topics – Categories
E.g. : <aiml>
<topic name=“the topic” > <category>
<pattern>PATTERN</pattern><that>THAT</that><template>TEMPLATE</
template> </category> </topic></aiml>
Example AIML Object
AIML Object<category>
<pattern>HELLO</pattern>
<template>Hi there!</template>
</category>
Chat SequenceUser: Hello!
Chat Bot: Hi There!
<category>
<pattern>YES</pattern>
<that>DO YOU LIKE MOVIES</that> <template>What is your favorite movie?</template>
</category>
Chat Bot: Do you like Movies?
User: Yes
Chat Bot: What is your favorite movie
Topics and Categories
Topic: an optional top-level element that contains category elements
Category: consists of an input question (pattern) and an output answer (template)
Types of Categories– Atomic Category– Default Category– Recursive Category
Atomic Category
Contains patterns that does not have wildcards “*” or “_”. Example:
Conversation: <category> <pattern>10 DOLLARS</pattern> <template> wow, what a cheap </template></category>
User: This watch is for 10 dollars
Chat Bot: Wow, what a cheap watch!
Default Category
Contains patterns that have wildcards “*” or “_”. Example:
Conversation:
<category>
<pattern>10 *</pattern> <template> It is ten.</template>
</category>
User: 10 dollars.
Chat Bot: It is ten.
Recursive category
Template calls the pattern matcher recursively Uses <srai> tag, that stands for symbolic recursion artificial
intelligence For example, In English there are different ways to ask about X:Describe x?Tell me about X?Do you know what X is? The knowledge is stored in the simplest way. Whatever the question is, it will be reduced to category like <What is>.
Input normalization
Substitution normalizationsAbbreviations such as "Mr." may be spelled out as "Mister" to avoid sentence-splitting at the period in the abbreviated form.
Sentence-splitting normalizationsRule: break sentences at periods. It relies upon substitutions performed in the substitution phase.
Pattern-fitting normalizationsRemove all characters that are not normal characters; like converting lowercase letters to uppercase .
<category>
<pattern>_ WHAT IS 2 AND 2</pattern>
<template>
<sr/><srai>WHAT IS 2 AND 2</srai>
</template>
</category>
<category>
<pattern>WHAT IS 2 *</pattern>
<template><random>
<li>Two.</li>
<li>Four.</li>
<li>Six.</li>
<li>12.</li>
</random></template></category><category>
<pattern>HALO</pattern>
<template>
<srai>HELLO</srai>
</template>
</category>
<category>
<pattern>HELLO</pattern>
<template> <random>
<li>Well hello there!</li>
<li>Hi there!</li>
<li>Hi there. I was just wanting to talk</li>
<li>Hello there !</li>
</random></template></category>
Example
Halo, What is 2 and 2
_ What is 2 and 2
</sr>
<srai> WHAT IS 2 AND 2 </srai>
Well hello there!Hi there!Hi there. I was justwanting to talk.Hello there !
WHAT IS 2 AND *
WHAT IS 2 *
TwoFourSix12
Hi There! Six
Question :
Answer :
HALO
HELLO
Graph-master – an example interpreter
AIML interpreter: tries to match word by word to obtain the largest pattern matching which is the best one.
Graph-master: an interpreter that models this behavior Contains a set of nodes called Node-mappers . Node-Mappers : map branches from each node where
branches represent the first words of all patterns. Each leaf node contains a template.
Flowchart for Pattern Matching
Search sub-graph rooted at child
node linked by ‘_’
Node-mapper Contains ‘X’?
Match?
Search sub-graph rooted at child
node linked by ‘X’ using input ‘tail’
Search sub-graph rooted at child
node linked by ‘*’
Try all remainingsuffixes of input
following ‘X’
Node-mapper Contains ‘_’?
Node-mapper Contains ‘*’?
Try all remainingsuffixes of input
following ‘X’
Match?
Match?yes
yes
yes
yes
yes
yes
no
no no
no
Some Observations
Priority order at every node:– ‘_’ wildcard, followed by– an atomic word, followed by– ‘*’ wildcard .
Patterns need not be ordered alphabetically The matching is word-by-word, not category-by-category Highly restricted form of depth-first search
Turing Test
Alan Turing proposed the Turing Test as a replacement for the question “Can machines think?”
Turing's aim is to provide a method to assess whether or not a machine can think.
The test– A man (A), a woman (B) and an interrogator (C) chat.– The objective of the interrogator is to determine which of the other
two is the woman– If a machine (bot) chats instead of A or B and fools the interrogator,
it has passed the Turing test.
Can It Answer All My Questions?
A Chat Bot has a limited number of patterns and responses. The AIML structure supports regular expressions In AIML, you can define recursive categories. The bot may sometimes give funny replies, but that depends
on the AIML spec, i.e. Its brain!
How to build a bot of your own
Components – An AIML Object Spec, AIML interpreter, and a responder!
A Chat Bot represents and models a character. The brain is the AIML file, that defines patterns and
corresponding replies A bot can be trained to be an Expert System about a special
theme – large data! Training data – Yahoo Chat!
What is a Chat Bot useful for?
Commercial chatter bots to help customers– At web-shops and e-commerce sites.– Bots to receive complaints from users, online
An interactive (talking) encyclopedia. Chatter bots administrating IRC-channels and Hotline
server. The Psychiatrist – the famous pronoun reversal trick Starship Titanic, a game created by the famous writer
Douglas Adams along with Terry Jones
Questions We Answered
What is it? Who wants it? Why? Since when is it around? How does it work? How do you test it? Can it answer all my questions? Can I make one of my own? Where can I put it to work?
A Chat Bot…
Clarifications
How powerful is JavaCC-built parser?– As long as one can use JavaCC's look-ahead specification to guide the
parsing where the LL(1) rules are not sufficient, JavaCC can handle any grammar that is not left-recursive.
Powerful than a yacc generated parser?– AIML is connected to a system that allows for learning new patterns and
putting them into a context – Context sensitive
Learning ?– Dialogue Corpora can be used to train a Chatbot! (See References)
Intelligent?– Even Turing tests have different levels and yet cannot finally decide
whether the system is intelligent or not. Nowadays a system is considered to be intelligent if it is able to mimic intelligent behaviour (e.g. within a specified domain).
References
The Anatomy of A.L.I.C.E.: Dr. Richard S. Wallace, http://www.alicebot.org/anatomy.html
Artificial Intelligence Markup Language (AIML), A.L.I.C.E. AI Foundation, http://alicebot.org/TR/2001/WD-aiml/
AIML Interpreter Overview 2004, http://www.aimlbots.com/en/aiml-interpreters.html
Computing machinery and intelligence, Alan Turing [1950], http://www.abelard.org/turpap/turpap.htm
Using Dialogue Corpora to Train a Chatbot (Bayan Abu Shawar, Eric Atwell) http://www.comp.leeds.ac.uk/andyr/research/papers/techreport2003_02.pdf