CS 660: Topics in Artificial Intelligence: Interactive Narrative

Spring 2023: Monday, Wednesday, and Friday online from 12:00 PM to 12:50 PM

Contents

Jump to today on the calendar.

Course Description

Storytelling comes naturally to people, and narrative is a fundamental cognitive tool that we use to communicate and make sense of the world. Computers are far behind people in their ability to understand and generate stories. General storytelling ability requires extensive common sense knowledge, but even telling stories in limited domains faces significant computational challenges. These challenges multiply when stories become interactive and must be adapted online in response to new or unexpected actions. Adaptive interactive narratives are a promising tool for video games, training simulations, intelligent tutoring systems, and virtual reality therapy, but we must first develop artificial intelligence applications capable of reasoning about and generating interactive stories in tandem with human partners.

This is a seminar-style course for graduate students interested in how artificial intelligence can be applied to create dynamic interactive narratives. Each meeting, students will present research papers on this topic and discuss them. With guidance from the instructor, students will define and execute a project to explore a topic of interest related to interactive narratives.

Learning Outcomes

After completing this course, students should:

Instructor

Prof. Stephen G. Ware
Department of Computer Science
Davis Marksbury Building, Room 307
sgware@cs.uky.edu
Office Hours: Monday, Tuesday, and Thursday from 4:00 PM to 5:00 PM

Prerequisites

This course is available to graduate students with consent of the instructor.

Text

There is no assigned textbook for this course. Readings will be taken from scientific conferences and journals and provided in advance to students.

Grading

Final grades will be determined by two types of assignments:

AssignmentPercentage
Attendance20%
Paper Presentations40%
Course Project40%

The focus of a seminar-style course is the reading and dicsussion of research papers on AI for interactive narrative systems. Since presentations and discussion are central, attendance is required. Students will be assigned to present papers from the calender below. The presenter is responsible for reading the paper and distilling the important information from it. The presenter should present the paper to the class (using slides or some other visual aid) and lead a discussion. Presentations will be graded according to this rubric.

Each student will also define a small project that applies AI to interactive storytelling in order to explore some topic of interest in more depth. At the midterm, students will have a chance to propose their project to their classmates and instructor to receive feedback. The project scope should be defined by the midterm, and the final deliverable is due at the conclusion of the course.

Policies

These policies are in place to maintain professionalism and mutual respect:

Academic Integrity

All students are expected to follow UK's code of academic integrity. Violations of this policy will be dealt with on a case-by-case basis, but punishment will be severe and may include failing the class and expulsion from the university.

Please be aware that copying code from another student or from an online repository such as GitHub without citing the original source is plagiarism and will be dealt with as such. Students are encouraged to build on the code of others, but copying a project whole cloth is cheating.

Students with Disabilities

Your instructor is happy to provide, on a flexible and individualized basis, accommodations for any student with a disability that makes it difficult to participate in the course or its assignments. Please visit the UK Disability Resource Center for more information.

Calendar

TopicAssignments
Monday, January 9
Introduction and Syllabus
  • Review course policies.
Wednesday, January 11
Narrative Intelligence
Friday, January 13
Narratology and Cognitive Science
Monday, January 16
Holiday
  • Dr. Martin Luther King Jr's Birthday
Wednesday, January 18
Survey of Story Generation
Friday, January 20
Discussion / Guest Speaker
Unit 1: Early Systems (up to 2000)
Monday, January 23
Survey of Early Systems
Wednesday, January 25
Story Grammars (1975 - 1979)
Friday, January 27
Tale-Spin and Author (1977 - 1981)
Monday, January 30
Discussion / Guest Speaker
Wednesday, February 1
Universe (1985)
Friday, February 3
Minstrel (1993)
Monday, February 6
Mexica (1999)
Wednesday, February 8
Mimesis (2000)
Friday, February 10
Discussion / Guest Speaker
Unit 2: Drama Management
Monday, February 13
Survey of Drama Management
Wednesday, February 15
The Oz Project and Façade
Friday, February 17
Optimization-Based Drama Management
Monday, February 20
Player Modeling
Wednesday, February 22
Narrative Mediation
Friday, February 24
Proactive Mediation
Monday, February 27
Discussion / Guest Speaker
Unit 2: Strong Autonomy Systems
Wednesday, March 1
Strong Autonomy
Friday, March 3
Social Physics
Monday, March 6
Discussion / Guest Speaker
Wednesday, March 8
Project Proposals
Friday, March 10
Simulation
Sunday, March 26
Academic Holiday
  • Spring Break
Monday, March 20
Sifting
Wednesday, March 22
Large-Scale Multi-Agent Storytelling
Unit 4: Strong Story Systems
Friday, March 24
Plans as Narrative
Monday, March 27
Planning for Narrative
Wednesday, March 29
Intentional Planning
Friday, March 31
Conflict Planning
Monday, April 3
Belief Planning
Wednesday, April 5
Discussion / Guest Speaker
Unit 5: Data-Driven Approaches
Friday, April 7
Annotated Text
Monday, April 10
Crowd-Sourcing
Wednesday, April 12
Deep Learning
Friday, April 14
Combining Planning and Deep Learning
Monday, April 17
Coherence in Neural Story Generation
Unit 6: Miscellaneous Topics
Wednesday, April 19
Project Checkpoint
  • Present the current state of your semester project and get feedback.
Friday, April 21
Cognitive Models in Narrative Plans
Monday, April 24
Story Embeddings
Wednesday, April 26
TBD
  • Paper chosen based on class interest.
Wednesday, May 3
Final Presentations
  • Present your projects to your instructor and classmates.
  • Consult the grading rubric.
  • Class meets from 1:00 PM - 3:00 PM