Humour-in-the-loop: Improvised Theatre with Interactive Machine Learning Systems

• Author / Creator

  Mathewson, Kory W.

• Improvisation is a form of live theatre where artists perform real-time, dynamic problem solving to collaboratively generate interesting narratives. The main contribution of this thesis is the development of artificial improvisation: improvised theatre performed by humans alongside intelligent machines. First, I present background underlying the art of improvisation and the scientific fields of interactive machine learning and dialogue generation. Then, I present Pyggy, the first experiment on live stage human-machine improvisation and A.L.Ex., the Artificial Language Experiment which addresses several key technical improvements over Pyggy. Improbotics is then presented which details audience evaluation of Turing test-inspired live improvised performance using A.L.Ex. Two novel contributions to machine-assisted narrative generation are then presented and discussed. The first of these contributions, Shaping the Narrative Arc, is a model incorporating an underlying narrative arc to improve response generation. The second contribution, dAIrector, synthesizes a plot graph with contextual information to generate contextual plot points and serve as director. The thesis concludes by discussing public reflections on live artificial improvisation performances from around the world and interesting future directions to explore. My work presents fundamental advances in human-machine interaction through the lens of improvised theatre which is the ideal test bed for collaboration between humans and intelligent machines.

• Subjects / Keywords

  • Computational Creativity
  • Interactive Machine Learning
  • Conversational Dialogue Systems
  • Human-Machine Interaction
  • Machine Learning
  • Artificial Intelligence
  • Improvisational Theatre

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-dn4w-bw61

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.