AI research in interactive narrative often lacks specificity as to the player experience it is trying to enable. In this paper, we consider a set of desirable elements from narrative and interactive experiences, and show by looking at playable experiences from industry and academia that combining them has the potential to be limited or self-defeating. To address these issues, we propose opportunistic storytelling, a set of design principles for near-term playable interactive narratives.

Extracting event knowledge from open-world survival video games is a promising domain to investigate the application of Machine Learning techniques to routine human decision making. This contrasts with and builds upon typical game-based decision making work that focuses on optimal behavior. We propose an Interaction Graph data structure that can be trained from game play to enable hybrid reasoning and statistical estimation about what events can happen in the world. This enables an agent to exhibit increasingly more reasonable behavior after low numbers of training runs. An implementation and initial experimental validation are presented.

In this paper, we discuss motivations for studying interactive narrative in shared, persistent worlds using the established conventions of quest-based MMORPGs. We present a framework for categorizing the various techniques used in these games according to the interaction between the world model and the quest model. Using this framework we generalize recent games to present a more dynamic world model, and investigate extensions to the quest model to support storytelling through adaptive quest narratives.

In this paper we explore the use of recursive cubic Hermite splines to mimic human movement in open world games. Human-like movement in an open world environment has many characteristics that are not optimal or directed towards clear, discrete goals. Using data collected from a simple MMORPG-like game, we use our spline representation to model human player movements relative to corresponding optimal paths. Using this representation, we show that simple distributions can be used to estimate control parameters to generate human-like movement across a population of agents in a novel environment.

In this paper we present a corpus of quest stories taken from a popular commercial Massively Multiplayer Online Role-Playing Game (MMORPG). These stories are open-ended narrative, but anchored to formal, in-game actions and entities, providing valuable constraint as a narrative corpus.

S. N. Srihari, C. Huang and H. Srinivasan, "Content-Based Retrieval of Handwritten Document Images," Knowledge Based Computer Systems (KBCS 2004), Hyderabad, India, December 2004. S. N. Srihari, C. Huang and H. Srinivasan, "Content-Based Retrieval of Handwritten Document Images," Knowledge Based Computer Systems (KBCS 2004), Hyderabad, India, December 2004.