September 4, 2003
I just finished a draft of an encyclopedia entry about “artificial intelligence.” It’s for the Routledge Encyclopedia of Narrative Theory and so, of course, it deals with how AI relates to narrative. Following Jill’s example, I have posted this draft in case anyone has comments on who I might have slighted, how I might have misrepresented AI, etc. I’d be greatful for any comments. It is as long as it can be, though, so I will have to cut things out if anything else is to go in there!
Revised: Thanks for your comments! I have replaced the first draft with the copy that I just submitted. (nm, 7 Sep 2003)
Artificial intelligence and narrative
Entry for The Routledge Encyclopedia of Narrative Theory
Artificial intelligence (AI) attempts to understand intelligence and to implement computer systems that can learn, reason, and make intelligent decisions. Philosophy, linguistics, and psychology are all involved in AI; computer science has had a central role. AI has dealt with narrative almost from the beginning. Narrative production and understanding are interesting types of intelligent behaviour; organizing stories into narrative may also be essential to human cognition (Schank 1990), a topic that scholars of *narrative intelligence consider. Conversational characters are one system at the intersection of AI and narrative. Other relevant systems are those that generate narratives, either by simulating an environment and what happens in it or by selecting which events will occur based on models of plot or character. Some of what has been learned in these systems has been employed in interactive systems, including interactive drama systems.
The term ‘artificial intelligence’ was coined in 1955. Arthur Samuel had already written a program that played checkers against itself and learned to play at the championship level. *Computer games have remained important to AI research and applications. One early and perhaps archetypal AI system in a different domain was the General Problem Solver (GPS) developed by Alan Newell and Herbert Simon in the late 1950s; it proved mathematical theorems. The standard introductory text (Russel and Norvig 2003) provides good historical notes while describing the essential mathematical and computational techniques of AI.
ELIZA (Weizenbaum 1966) was the first conversational character. The system communicated in text and simulated a Rogerian psychotherapist. Although it simply matched patterns in the user’s input and looked up responses, the system created the sense of a character and often elicited narratives from users; some found it compelling for psychotherapeutic, literary, or dramatic reasons (Murray 1997:214-247). Its successors included the 1971 simulated schizophrenic PARRY, an academic project by Ken Colby, and the 1984 commercial program Racter by William Chamberlain. A book of poems, The Policeman’s Beard is Half Constructed, was attributed to Racter.
SHRDLU (Winograd 1972) used text and graphics to simulate a robot that could rearrange blocks. The system could answer questions about what had happened and could narrate the actions that had resulted in the current configuration; it was an important ancestor of interactive fiction such as the 1975-76 Adventure and the 1977-78 Zork. Several later systems had the generation and narration of stories as their main goal. The first of these was TALE-SPIN (Meehan 1976), which used planning to generate fables about animals with simple drives and goals. The system’s memorable, amusing errors revealed how difficult it is to automatically generate interesting stories. Michael Lebowitz’s 1984 UNIVERSE refined this approach and enhanced the representation of characters (embellishing certain stereotypes) to generate soap-opera narratives. MINSTREL (Turner 1994) was a similar system to generate Arthurian tales; it was able to get ‘bored’ and move on to other topics. A recent automatic storyteller is BRUTUS (Bringsjord and Ferrucci 2000), a system that uses a formal model of betrayal and has sophisticated abilities as a narrator. These story-generating systems do not accept user input as they narrate, but they show how AI can be deeply involved with *digital narrative even in non-interactive systems.
In the early 1990s, interactive narrative systems that used AI techniques were developed at Carnegie Mellon University’s Oz Project. Graphical and all-text projects considered how parsing natural language, generating surface texts, and representing the emotional states of characters could be handled in a dramatic framework. One thread of this project continued in the work of Joe Bates’s company Zoesis, while Michael Mateas continued the Oz Project’s work at CMU, completing a graphical, Aristotelian, interactive drama, Façade, in collaboration with Andrew Stern (Mateas 2002). Façade does not have an all-powerful ‘director’ or completely autonomous characters; it allows the characters in the drama to cooperate (even when they are fighting) to attain common goals (e.g., ‘portray a fight and make the user uncomfortable.’)
The systems above almost all represent story elements and ways of narrating explicitly, using techniques associated with rule-based or symbolic AI, also called ‘good old-fashioned AI’ (GOFAI). Since the 1990s much work in AI has been done in a different framework, successfully employing statistical methods and connectionist principles. Such approaches, although effective, are often unable to provide an explicit, human-understandable representation of the system’s knowledge or an explanation for its actions, which some see as a disadvantage for work with narrative. Statistical systems have been used to generate poetry (e.g., Jon Trowbridge’s free system Gnoetry) and in some work involving narrative and cognition (e.g., the computational neuroscience project Shruti at Berkeley). Whether GOFAI will continue to be favoured for creative narrative work or whether more recent AI techniques will be used in these endeavours as well remains to be seen.
References and Further Reading
Bringsjord, Selmer and David A. Ferrucci (2000) Artificial Intelligence and Literary Creativity: Inside the Mind of BRUTUS, a Storytelling Machine. Hillsdale, NJ: Lawrence Erlbaum.
Mateas, Michael (2002) ‘Interactive Drama, Art, and Artificial Intelligence.’ Ph.D. Thesis. Technical Report CMU-CS-02-206, School of Computer Science, Carnegie Mellon University.
Meehan, James (1976) ‘The Metanovel: Writing Stories by Computer.’ Ph.D. thesis, Yale University.
Murray, Janet (1997) Hamlet on the Holodeck: The Future of Narrative in Cyberspace. New York: Free Press.
Russell, Stuart, and Peter Norvig (2003) Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice Hall.
Ryan, Marie-Laure (1991) Possible Worlds, Artificial Intelligence, and Narrative Theory. Bloomington: Indiana University Press.
Schank, Roger C. (1990) Tell Me a Story: A New Look at Real and Artificial Memory. New York: Charles Scribner.
Turner, Scott R. (1994) The Creative Process: A Computer Model of Storytelling and Creativity. Hillsdale, NJ: Lawrence Erlbaum.
Weizenbaum, Jospeh (1966) ‘Eliza — a computer program for the study of natural language communication between man and machine,’ Communications of the ACM, 9:36-45.
Winograd, Terry (1972) Understanding Natural Language. New York: Academic Press.