IRC Hacks [Electronic resources] نسخه متنی

Hack 62 An Artificial Intelligence Bot

Use the JMegaHal package in a PircBot-based IRC
bot that learns from and chats with other users.

I RC is not just a place where people hang
out in channels, chatting with one another. It is also a valuable
learning zone. Knowledgeable users populate certain channels.
Interacting with these users makes it possible to learn new facts and
share in a wealth of expert information on a particular subject. This
is obviously useful to human users, but what about bots? Can they too
learn from what they see on IRC? Is it possible to mimic the behavior
of a human user?

From a learning point of view, one appealing thing about IRC is that
you can join a channel and quietly observe real humans talking to one
another. You can learn a lot while lurkingand so can a bot.
One popular pastime is to try to make conversation bots that respond
intelligently to what is being said by the humans around it. What
better way could there be of teaching such bots than by leaving them
in a busy channel, learning from what real users are saying?

9.6.1 Markov Modeling

One
simple way of modeling each sentence
generated by a human user is to break it down into tokens. In the
simplest case, each word in the sentence is a token. After several
sentences are "learned," an attempt
can be made to create new sentences based on what has been observed.
As humans generate more sentences, tokens that are used to start and
end sentences become recognizable, as do which tokens are likely to
precede or follow any particular token. All of these links form a
graphlike structure that can be navigated from start to finish, with
each random walk generating a different sentence that nearly makes
logical sense. Due to the nature of this model, it is independent on
the language spoken, although strange results may be observed when it
learns more than one language at a time. Figure 9-5
shows the kind of data structures that form in a Markov chain.

Figure 9-5. The data structures present in a Markov chain

There is a simple Java Applet that demonstrates and visualizes the generation of these graphs at http://www.jibble.org/dynamicgraph.php.

9.6.2 JMegaHal

MegaHal is
a more advanced model that improves the quality of the generated
sentences by gathering tokens into sequences of four and remembering
which tokens precede
and follow these sequences. Tokens consist of words and punctuation
between words. A full description of the model can be found at
http://www.megahal.net.

JMegaHal is a simple Java
implementation of MegaHal and can be found at http://www.jibble.org/jmegahal. This also
generates a fourth-order Markov chain to generate sentences in
response to user input. It is these higher orders that ensure the
output makes more sense than simpler implementations, but, of course,
this will also depend on where your bot is learning its sentences.

Because the token set can include the whitespace and punctuation
between words, the model is likely to preserve punctuation styles.
However, because IRC channels typically contain more than one user,
you probably won't notice any recognizable style, as
it will be learning from everybody.

As an example, given the following two sentences to learn from:

The dog sat on the mat.
There was a dog sat in the bushes.

JMegaHal could possibly come out with four different sentences:

The dog sat on the mat.
There was a dog sat in the bushes.
The dog sat in the bushes.
There was a dog sat on the mat.

9.6.3 The Code

In this hack, we use the JMegaHal package to learn sentences and
generate replies. We will then combine it with the PircBot package
[Hack #35] to create an IRC bot
that can learn from other IRC users and hold wacky conversations with
them.

9.6.3.1 A simple example

The

JMegaHal package is supplied in a JAR
file, so it is easy to integrate into any Java program, including an
IRC bot. Make sure you import
org.jibble.jmegahal.*; in any classes that will
use it.

JMegaHal hal = new JMegaHal( );
// Teach it some sentences.
hal.add("Hello, my name is Paul.");
hal.add("This is a sentence.");
// Note that the more sentences you add, the more sense it will make...
// Make JMegaHal generate a sentence.
String sentence1 = hal.getSentence( );
// Get another sentence, with the word "jibble" in it (if possible).
String sentence2 = hal.getSentence("jibble");

Notice the getSentence method can take a String as
an optional argument. If you want to generate random sentences all
about pie, then you might want to call
hal.getSentence("pie"). This ensures that all
generated sentences include the word
"pie" somewhere. If JMegaHal has
not yet learned anything about pie, it will choose some other random
token.

One thing to consider with a chat bot is telling it when to respond.
If you make it respond to every message, the other users in the
channel will very quickly get fed up with it and kick it out. One
safe option is to make it respond only to messages that contain its
nickname but to learn from all other messages.

9.6.3.2 Combining JMegaHal and PircBot

Combining JMegaHal and PircBot is very easy. If
anybody utters the bot's nickname, it should respond
with a randomly generated sentence from the JMegaHal object. All
other messages that do not contain the bot's
nickname will be used to teach it more sentences. In the following
simple implementation, the bot is seeded with a starting sentence in
the constructor, so it will always be able to respond with this if it
has not learned anything else.

Create a file called
JMegaHalBot.java:

import org.jibble.pircbot.*;
import org.jibble.jmegahal.*;
public class JMegaHalBot extends PircBot {
private String name;
private JMegaHal hal;
public JMegaHalBot(String name) {
setName(name);
hal = new JMegaHal( );
// Add at least one sentence so the bot can always form a reply.
hal.add("What is the weather like today?");
}
public void onMessage(String channel, String sender,
String login, String hostname, String message) {
if (message.toLowerCase( ).indexOf(getNick( ).toLowerCase( )) >= 0) {
// If the bot's nickname was mentioned, generate a random reply.
String sentence = hal.getSentence( );
sendMessage(channel, sentence);
}
else {
// Otherwise, make the bot learn the message.
hal.add(message);
}
}
}

Now you just need to create a main method to construct the bot and
tell it what nickname to use. The main method will also tell the bot
which server to use and which channel to join.

This bot can run in multiple channels, but bear in mind that
sentences learned in one channel could end up appearing in other
channels.

Create the file

JMegaHalBotMain.java:

public class JMegaHalBotMain {
public static void main(String[] args) throws Exception {
JMegaHalBot bot = new JMegaHalBot("Chatty");
bot.setVerbose(true);
bot.connect("irc.freenode.net");
bot.joinChannel("#irchacks");
}
}

9.6.4 Running the Hack

To compile and run the hack, you will need
both the JMegaHal.jar and
pircbot.jar files. Both of these must be in the
classpath when compiling and running. To compile the bot, type the
following:

C:\java\JMegaHalBot> javac -classpath .;pircbot.jar;JMegaHal.jar *.java

To run the bot:

C:\java\JMegaHalBot> java -classpath .;pircbot.jar;JMegaHal.jar JmegaHalBotMain

The bot will echo everything it's doing to the
standard output, and you can start chatting with it as soon as
it's joined the channel.

9.6.5 The Results

Figure 9-6 shows the JMegaHalBot in action. The bot
will obviously learn more if it is placed in a busy channel.
Don't expect it to come out with anything too
profound or unique until it has learned more than a hundred
sentences.

Figure 9-6. The JMegaHalBot trained with the contents of this hack

Although you probably want your bot to learn as fast as it can,
it's not always a good idea to place it in an
enormously busy channel, as it may not get noticed. Be patient and
wait for the best results.