Difference between revisions of "Computational Models"

Computational Models

Each IS system has its own computational model that serves as a basis for its implementation. Such models are often complex and hybrid; borrowing from several computational approaches. Within these models, we tried to identify basic computational models that were not attached to a given IS system but still had a sufficient level of generality to be useful for a large range of systems.

The computational models presented here come from various families: Models for AI planning, Discrete Event Models for control, Logic and proof-theory, Stochastic models, etc. Such diversity reflects the different approaches in the field of AI.

For each model we present:

• Background: formal foundation, initial goals of the model.
• Description: short overview of the theory.
• Application to Interactive Storytelling: how the computational model has been or could be used in IS.
• Examples: Story examples modeled with this computational model (when available).
• References

Models

• Bayesian networks
• ISRST (Interactive Storytelling model using RST)
• Linear logic
• Planning Domain Definition Language (pddl)
• Petri nets
• Sceneflows