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|Title:||Agent mediated interactive storytelling||Authors:||Cai, Yundong||Keywords:||DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence||Issue Date:||2011||Source:||Cai, Y. D. (2011). Agent mediated interactive storytelling. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Interactive storytelling in the virtual environment attracts many interests from researchers and educators in recent years. People are engaged in the storytelling as active participants by interacting with virtual characters as well as story director (storyteller), rather than acting as passive audiences in the conventional storytelling. However, it is a great challenge to create an immersive interactive storytelling system in the virtual environment from scratch with an engaging storyline and believable characters, especially for the novice developers without many programming skills. The current interactive storytelling methodologies (e.g. plot-based interactive storytelling and character-based interactive storytelling) cannot ensure the story plot coherence and character believability simultaneously. The director and characters are not autonomous and intelligent enough to handle dynamic user interactions and context changes. In the thesis, we propose a novel Agent-Oriented Methodology for Interactive Storytelling (AOMIS) to facilitate novices to develop an immersive interactive storytelling system from a story. It generates both the story plot and the character behaviors as agent goals seamlessly in real-time. Human-like agent is a promising solution for the intelligent director and characters in the interactive virtual storytelling with the high-level goal automation besides the low-level behavior automation. A multi-agent system (MAS) has been constructed for illustrating the hybrid model, which involves a scriptwriter agent to draft the nonlinear storylines, a director agent to select the storyline, virtual character agents to perform the story scenes, and other supporting agents.||URI:||https://hdl.handle.net/10356/45767||DOI:||10.32657/10356/45767||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCSE Theses|
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Updated on May 9, 2021
Updated on May 9, 2021
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