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Beyond AIML: Chatbots 102
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Beyond AIML: Chatbots 102

August 14, 2008 Article Start Page 1 of 6 Next

[Industry veteran Wilcox is creating NPC text chatbots for Avatar Reality's Blue Mars, and this technical article discusses his adventures in AI markup language to create effective human-text interaction.]

A beginning chatbots course (Chatbots 101) would teach AIML. AIML is the AI markup language based on XML, used for making chatbots.

It has its roots in Dr. Wallace's A.L.I.C.E. chatbot, which has led to PandoraBots and a lot of spin-off bots based on standardized AIML. As a standard, AIML made it possible for many people to work on chatbots more easily.

Avatar Reality (, a virtual world company built from the ashes of the Square USA Honolulu office, wants to use chatbots to represent a user while that user is absent from the Blue Mars world - a CryEngine 2-using online environment set on a terraformed Mars. My job is to provide them with the appropriate chatbot technology.

AIML is one such technology, but for my purposes it is simply a woefully inadequate tool and once again I find myself building a new scripting language (see Reflections on Building Three Scripting Languages, a prior Gamasutra article). Hence Chatbots 102.

Historical Perspective

The conversations-with-a-computer genre began in the 1960's with Eliza, the computer parody of a Rogerian psychiatrist. Using a mere 53 rules, and by substituting part of the user's input back into an output question, the program gave an illusion of interacting as a human.

It had to always ask questions - because that's the best way to hide the fact that it knew absolutely nothing. Asking questions takes advantage of the fact that humans are good at substituting their own rich interpretations into simple words in questions that have any vague connection at all to the topic at hand.

Eliza evolved into most of the chatbots of today. They take user input and, using tens of thousands of rules, generate output. They differ from Eliza in that they usually have some built-in world knowledge, so that if you ask them if they like chocolate you might get a straight "yes" answer instead of "Why do you think of chocolate right now?"

In a different vein, meaning-based human text interaction with computers began with the adventure games of the 1970s (Zork is a great example). Humans were given an extremely limited grammar and vocabulary and interacted by telling the system what action to take using what object and got back a canned text description of what happened. It was very popular because the human had a set of choices that could be made, had interesting material to read, pretended to be in a magical setting, and got to solve puzzles.

The modern video game has evolved to where the user controls an avatar by mouse or joystick and gets visual feedback. They have a limited real world with physics, though the computer does not generally talk or reason about it.

But chatbots and meaning-based interaction don't currently go hand in hand in most video games anymore. However, there is lots of room for developing better NPC characters.

Meanwhile, a chatbot like A.L.I.C.E. is an expert system. An expert system can perform interesting to significant tasks when it has a limited domain and 30,000 to 50,000 rules for a brain. Many more recent chatbots claim magical AI abilities, but you should take those claims with a ton of salt. Descriptions of chatbot capabilities and development systems are usually gross exaggerations.

So where are there pitfalls in building a chatbot? Getting reliable human interaction out of a computer is a tar pit waiting to trap any programmer. The quantity of human knowledge is vast.

The Cyc project has spent over 100 man-years working on just organizing knowledge, and they have a long way to go. Chatbots do not have to master all that. They attempt to simulate interesting and vaguely intelligent conversation by other means. Current ones can be entertaining, but you can quickly make them look stupid. Future ones, using additional technology, can look slightly less stupid.

So where are there opportunities in building a chatbot? The dominant chatbots were started almost a decade ago, so their design goals and decisions were made some time ago. Technology has evolved.

First, hardware has changed. Machines are faster and storage is massive, and for all practical purposes, free. Second, in the past decade natural language processing has created parsers that often can correctly parse a sentence (though this is less valuable in chat, since it is often not grammatical).

Third, the internet provides ubiquitous connections among people, information, and software. Fourth, extensive amounts of human knowledge have been gathered and made accessible via the internet (including Google and Wikipedia). Fifth, there have been a lot of projects in ontologies, knowledge representation, etc. These are all things that current chatbots do not use to best advantage.

I am currently working on incorporating all these into the AR chatbot and maybe I can write about that towards the end of this year. But this article isn't about those things. It is merely about a better scripting language than AIML.

Article Start Page 1 of 6 Next

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