Tag: Artificial Intelligence
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Salience as a Narrative Planning Step Cost Function
Psychological research has demonstrated that as we experience a story several features affect the salience of its events in memory. These features correspond to who? where? when? how? and why? questions about those events. Computational models of salience have been used in interactive narratives to measure which events people most easily remember from the past…
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Multi-Agent Narrative Experience Management as Story Graph Pruning
In interactive narratives, experience management is used to control the world and the NPCs a player interacts with, encouraging particular types of stories or discouraging others. The space of all stories in a narrative can be understood as a story graph, with story states as nodes and actions in the story as directed edges. In…
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Narrative Planning for Belief and Intention Recognition
Planning algorithms generate sequences of actions that achieve a goal, but they can also be used in reverse: to infer the goals that led to a sequence of actions. Traditional plan-based goal recognition assumes agents are rational and the environment is fully observable. Recent narrative planning models represent agents as believable rather than perfectly rational,…
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Combining Intentionality and Belief: Revisiting Believable Character Plans
In this paper we present two studies supporting a plan-based model of narrative generation that reasons about both intentionality and belief. First we compare the believability of character plans taken from the spaces of valid classical plans, intentional plans, and belief plans. We show that the plans that make the most sense to humans are…
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Causal Link Semantics for Narrative Planning using Numeric Fluents
Narrative planners would be able to represent richer, more realistic story domains if they could use numeric variables for certain properties of objects, such as money, age, temperature, etc. Modern state-space narrative planners make use of causal links—structures that represent causal dependencies between actions—but there is no established model of a causal link that applies…
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Influencing User Choices in Interactive Narratives using Indexter’s Pairwise Event Salience Hypothesis
Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience—or prominence in memory—of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that a past event is more salient if it…
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A Possible Worlds Model of Belief for State-Space Narrative Planning
What characters believe, how they act based on those beliefs, and how their beliefs are updated is an essential element of many stories. State-space narrative planning algorithms treat their search spaces like a set of temporally possible worlds. We present an extension that models character beliefs as epistemically possible worlds and describe how such a…
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Asking Hypothetical Questions about Stories using QUEST
Many computational models of narrative include representations of possible worlds—events that never actually occur in the story but that are planned or perceived by the story’s characters. Psychological tools such as QUEST are often used to validate computational models of narrative, but they only represent events which are explicitly narrated in the story. In this…
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Predicting User Choices in Interactive Narratives using Indexter’s Pairwise Event Salience Hypothesis
Indexter is a plan-based model of narrative that incorporates cognitive scientific theories about the salience of narrative events. A pair of Indexter events can share up to five indices with one another: protagonist, time, space, causality, and intentionality. The pairwise event salience hypothesis states that when a past event shares one or more of these…
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Fast and Diverse Narrative Planning through Novelty Pruning
Novelty pruning is a simple enhancement that can be added to most planners. A node is removed unless it is possible to find a set of n literals which are true in the current state and have never all been true in any of that plan’s previous states. Expanding on the success of the Iterated…