Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
A Goal-Based Model of Personality for Planning-Based Narrative Generation
Authors: Julio Bahamon, Camille Barot, R. Michael Young
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present an approach to incorporate interesting and compelling characters in planning-based narrative generation. The approach is based on a computational model that utilizes character actions to portray these as having distinct and well-deο¬ned personalities. In this paper we present a computational model aimed at facilitating the inclusion of compelling characters in narratives that are automatically generated by a planning-based system. |
| Researcher Affiliation | Academia | Julio C esar Baham on, Camille Barot, and R. Michael Young North Carolina State University, Liquid Narrative Research Group Campus Box 8206, Raleigh NC 27695-8206, USA EMAIL, EMAIL |
| Pseudocode | No | The paper describes the narrative generation mechanism in prose and through definitions but does not provide a formal pseudocode or algorithm block. |
| Open Source Code | No | The paper does not provide any information about open-source code availability. |
| Open Datasets | No | The paper is theoretical and does not describe the use of any publicly available or open dataset for training or evaluation. |
| Dataset Splits | No | The paper does not describe any experimental setup or dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper does not describe any experimental setup, and therefore does not provide hardware specifications. |
| Software Dependencies | No | The paper does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper does not describe an experimental setup, including hyperparameters or system-level training settings. |