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Moody5: Personality-biased agents to enhance interactive storytelling in video games
Open accessAbstract
In story-driven video games, such as Role-Playing Games (RPGs), a static and repetitive interaction with Non-Player Characters (NPCs) can negatively impact fun and immersion. On the contrary, an NPC able to show emotions and endowed with a personality that matches its behavior can keep the user engaged for a longer time. Unfortunately, this aspect has not yet been fully investigated. We propose Moody5, a preliminary solution designed to help game designers create “personality-biased” agents able to interact in sensible ways in the framework of interactive storytelling. In particular, it supports the creation of agents that exploit the Goal-Oriented Action Planning (GOAP) technique to reach their goals but whose chain of actions and quality of the interaction with the player are dynamically affected by personality and emotions. To obtain this result, we have borrowed ideas from the Big Five theory [1] and the Emotion Facial Action Coding System (EMFACS) by Ekman & Friesen [2]. We validated the proposed solution in a narrative test scenario inspired by the Harry Potter universe. Our preliminary survey demonstrated that Moody5 could improve the gameplay experience and replay value while providing a helpful Unity plugin for game developers.
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“Static and repetitive interactions with the environmentsuch as with key items, events, and non-playable characters (NPCs)-can negatively impact players experiences and their desire to replay games (Garavaglia et al. 2022).”
From PANGeA: Procedural Artificial Narrative Using Generative AI for Turn-Based, Role-Playing Video Games (2024) · cites this paper as Garavaglia et al. 2022
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In the citing paper
“PANGeA's novel validation system is a key feature supporting these features, as it addresses the challenges behind processing free-form text input and maintaining narrative coherence (Kumaran et al. 2023; Garavaglia et al. 2022; Park et al. 2023).”
From PANGeA: Procedural Artificial Narrative Using Generative AI for Turn-Based, Role-Playing Video Games (2024) · cites this paper as Garavaglia et al. 2022
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Cites
Russell, J. A. (1994) · Psychological Bulletin · doi:10.1037/0033-2909.115.1.102 · Cited by 1,640 · cited 2×
“Moody5’s emotion model, as described in Subsection III-A3, adopts Ekman’s EMFACS approach to simulate primary emotions in NPCs [2].”
Method
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Sorted by citations
PANGeA: Procedural Artificial Narrative Using Generative AI for Turn-Based, Role-Playing Video Games
Buongiorno, S., Klinkert, L., Zhuang, Z., Chawla, T., & Clark, C. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v20i1.31876 · Cited by 37
Metadata
- Authors
- Garavaglia, F., Nobre, R. A., Ripamonti, L. A., Maggiorini, D., & Gadia, D.
- Affiliations
- University of Milan (IT)
- Venue
- 2022 IEEE Conference on Games (CoG)
- Publisher
- IEEE
- Published
- 2022-08-21
- Pages
- 175-182
- OpenAlex
- W4296474773
- Cited by
- 7
- References
- 1
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 5
- FWCI
- 0.83
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- IEEE Conference on Games (CoG) (publishedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
- Social Sciences › Sociology and Political Science › Digital Games and Media
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- non-player characters, interactive storytelling, role-playing games, Big Five personality traits, facial action coding system, emotion modeling, player engagement, immersion, game development tools
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