Uludağlı, M. Çağkan

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14365/7613
Name Variants
Uludagli, Muhtar C
Uludağlı, Muhtar Çağkan
Uludagli, M. Cagkan
Uludagli, Cagkan
Job Title
Email Address
cagkan.uludagli@ieu.edu.tr
Main Affiliation
05.05. Computer Engineering
Status
Current Staff
Website
https://homes.izmirekonomi.edu.tr/culudagli/
ORCID ID
0000-0003-1018-650X
Scopus Author ID
57203904849
Turkish CoHE Profile ID
FED57DCDF5C85B6F
Google Scholar ID
tYZsbfQAAAAJ
WoS Researcher ID
AAA-4930-2022
Files
Cagkan_Uludagli.jpg (10.68 KB)

Sustainable Development Goals

Documents

5

Citations

49

h-index

2

Go to Scopus profile
Documents

4

Citations

27

Go to WoS profile
Scholarly Output

5

Articles

3

Views / Downloads

21/1122

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

14

Scopus Citation Count

33

WoS h-index

1

Scopus h-index

1

Patents

0

Projects

0

WoS Citations per Publication

2.80

Scopus Citations per Publication

6.60

Open Access Source

2

Supervised Theses

0

JournalCount
Current Page: 1 / NaN

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

2022 - 20255
Reset filters

Settings

Scholarly Output Search Results

Now showing 1 - 5 of 5
  • Thumbnail Image
    Article
    Citation - WoS: 13
    Citation - Scopus: 30
    Non-player character decision-making in computer games
    (Springer, 2023) Uludağlı, Muhtar Çağkan; Oğuz, Kaya
    One of the most overlooked challenges in artificial intelligence (AI) for computer games is to create non-player game characters (NPCs) with human-like behavior. Modern NPCs determine their actions in different situations using certain decision-making methods, enabling them to change the current state of the game world. In this paper, we survey current decision-making methods used by NPCs in games, identifying five categories. We give detailed overview of these five categories and determine the previous studies that belong to each of these categories. We also discuss the hybrid methods which are the combinations of different decision-making methods and the frameworks that are created for NPC decision-making. As a result of this analysis, we create a taxonomy table based on these covered studies. Lastly, the challenges faced in our study and future possibilities for improvement are described.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    A Social Network Generator for Games Evaluated Against a Real Npc Network With Gpt-Generated Node Attributes
    (Institute of Electrical and Electronics Engineers Inc., 2024) Uludaglı, M.Ç.; Oğuz, K.
    This study presents a novel approach for generating social networks for non-player characters (NPCs) in video games through an automated graph generation method. By leveraging existing methodologies and enhancing them in our generator, the aim is to produce NPC networks that closely mimic the structure and properties of agent social networks observed in video games. The method integrates attribute-aware graph generation to ensure realistic and complex network interactions among NPCs. A comparative analysis with an NPC network of a video game which has ChatGPT-generated node attributes demonstrates the effectiveness of our generator in creating more interconnected and dynamic NPC social structures. The findings suggest that our generator is a robust tool for researchers and game developers to simulate NPC interactions, thus enhancing the narrative and interactive depth of video games. © 2024 IEEE.
  • Thumbnail Image
    Article
    Citation - Scopus: 1
    From Attributes To Communities: a Novel Approach in Social Network Generation
    (Peerj inc, 2024) Uludagli, Muhtar cagkan; Oguz, Kaya
    Generating networks with attributes would be useful in computer game development by enabling dynamic social interactions, adaptive storylines, realistic economic systems, ecosystem modelling, urban development, strategic planning, and adaptive learning systems. To this end, we propose the Attribute-based Realistic Community and Associate NEtwork (ARCANE) algorithm to generate node-attributed networks with functional communities. We have designed a numerical node attribute-edge relationship computation system to handle the edge generation phase of our network generator, which is a different method from our predecessors. We combine this system with the proximity between nodes to create more life-like communities. Our method is compared against other node-attributed social network generators in the area with using both different evaluation metrics and a real-world dataset. The model properties evaluation identified ARCANE as the leading generator, with another generator ranking in a tie for first place. As a more favorable outcome for our approach, the community detection evaluation indicated that ARCANE exhibited superior performance compared to other competing generators within this domain. This thorough evaluation of the resulting graphs show that the proposed method can be an alternate approach to social network generators with node attributes and communities.
  • Thumbnail Image
    Conference Object
    A Preliminary Analysis of Gamification on Assembly Language Programming Education
    (Dechema e.V., 2025) Uludağlı, Muhtar Çağkan
  • Thumbnail Image
    Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Virtual Body Anthropomorphism Increases Drift in Self-Location: Further Support for the Humanoid Shape Rule
    (Wiley, 2022) Tekgun, Ege; Uludagli, Muhtar C.; Akcan, Hüseyin; Erdeniz, Burak
    Previous studies on bodily self-consciousness (BCS) have shown that self-location and body ownership are prone to changes based on the perceptual appearances of the fake virtual body. In the current study with 36 participants, we assessed the influence of virtual avatar anthropomorphism and the synchronicity of the visuo-tactile stimulation on self-location using a virtual reality full-body illusion experiment. During the experiment, half of the participants observed a gender-matched full-body humanoid avatar from a first-person perspective (1PP) and the other half observed a less anthropomorphic full-body cubical avatar from 1PP while they were receiving synchronous and asynchronous visuo-tactile stimulation. Results showed a significant main effect of the synchronicity of the visuo-tactile stimulation and avatar body type on self-location but no significant interaction was found between them. Moreover, the results of the self-report questionnaire provide additional evidence showing that participants who received synchronous visuo-tactile stimulation, experienced not only greater changes in the feeling of self-location, but also, increased ownership, and referral of touch. Our results provided further support for the previous findings that showed evidence for the effect of virtual avatar appearance on BCS.