Your browser does not support JavaScript!

Home    Search  

Results - Details

Search command : Author="Στεφανίδης"  And Author="Κωνσταντίνος"

Current Record: 4 of 72

Back to Results Previous page
Next page
Add to Basket
[Add to Basket]
Identifier 000461061
Title Autonomia: a knowledge-based framework for realistic agent behaviours in dynamic video game environments
Alternative Title Autonomia: ένα προγραμματιστικό πλαίσιο που βασίζεται στην γνώση για ρεαλιστικές συμπεριφορές πρακτόρων σε δυναμικά περιβάλλοντα βιντεοπαιχνιδιών
Author Περβολαράκης, Ζαχαρίας Ε.
Thesis advisor Στεφανίδης, Κωνσταντίνος
Reviewer Μαγκούτης, Κωνσταντίνος
Ζαμπούλης, Ξενοφών
Abstract Video games are a popular form of entertainment that offer interactive and immersive experiences to the players. A key element of these experiences is the presence of non-player characters (NPCs), which are autonomous agents that populate the game world and interact with the player and the environment. NPCs can enhance the realism and diversity of the game scenarios by exhibiting human- like behaviours that are consistent, adaptive and believable. However, creating such behaviours is a complex and challenging task that requires a combination of artificial intelligence (AI) techniques and game design principles. Current methods and frameworks for NPC decision-making often rely on predefined scripts or rules that limit the NPC’s capability to adapt to dynamic situations. Moreover, NPCs usually lack autonomy, as they are unable to pursue their own goals, as well as to interact with other NPCs or the player. Therefore, there is a need for novel approaches that can improve the credibility and adaptability of NPC behaviours in video games. This work introduces Autonomia, an innovative knowledge-based framework for realistic agent behaviours in dynamic video game environments. Autonomia is deeply rooted in the Theory of Mind (ToM), leveraging a knowledge graph to depict the world's state, with each NPC possessing a replica of this world state in its “memory”. This “memory” is designed to support higher orders of ToM while constantly evolving as the NPC perceives the world around it and interprets events. Autonomia uses a modular system to define the functionality and behaviour of different types of nodes in the graph, such as physical objects, animals or people. The framework as structured, allows NPCs to dynamically react to changes in the environment purely based on its ability to perceive and hold memory. In this context, Autonomia introduces a new way to model behaviours and goals, enabling them to be treated as knowledge that can be communed, discovered or even forgotten just like any other part of the NPC's “memory”. Basing everything on their acquired knowledge, NPCs utilize a Goal-Oriented Action Planning (GOAP) algorithm to come up with plans in any dynamic environment. Lastly, an implementation of Autonomia is provided for the Unity game engine, including the “Prometheus Tavern” case study, on which a two-part expert-based evaluation was conducted. The first part confirmed that the provided features and the architecture of the Autonomia framework deliver solutions that can improve the credibility of NPC behaviours, whereas the second showed that the agents of the system have the capability to adapt to their environment and behaviour in a realistic manner.
Language English
Subject Autonomous Agents
Game AI
NPC
NPC Behaviours
Issue date 2023-12-01
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/3/3/2/metadata-dlib-1701959625-154345-17277.tkl Bookmark and Share
Views 907

Digital Documents
No preview available

No permission to view document.
It won't be available until: 2024-06-01