A Procedural Generation Framework for a Robot Construction Game

被引：0
|
作者：
Vinciguerra, Michele [1 ]
Thompson, Tommy [1 ]
机构：
[1] Univ Derby, Dept Comp & Math, Derby DE22 1GB, England
来源：
2015 7TH COMPUTER SCIENCE AND ELECTRONIC ENGINEERING CONFERENCE (CEEC) | 2015年
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper explores a framework to permit the creation of modules as part of a robot creation and combat game. We explore preliminary work that offers a design solution to generate and test robots comprised of modular components. This current implementation, which is reliant on a constraint-driven process is then assessed to indicate the expressive range of content it can create and the total number of unique combinations it can establish.
引用
收藏
页码：213 / 218
页数：6
相关论文
共 50 条
  • [31] Intrinsically Motivated Reinforcement Learning: A Promising Framework for Procedural Content Generation
    Shaker, Noor
    [J]. 2016 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG), 2016,
  • [32] Framework for the adaptation of the characteristics of the rhetoric to the construction elements of the video game
    Legeren-Lago, Beatriz
    Crespo-Pereira, Veronica
    [J]. 2019 14TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2019,
  • [33] Cooperative Game Theoretic Framework for Joint Resource Management in Construction
    Asgari, Sadegh
    Afshar, Abbas
    Madani, Kaveh
    [J]. JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2014, 140 (03)
  • [34] A deep learning framework for realistic robot motion generation
    Dong, Ran
    Chang, Qiong
    Ikuno, Soichiro
    [J]. NEURAL COMPUTING & APPLICATIONS, 2023, 35 (32): : 23343 - 23356
  • [35] A deep learning framework for realistic robot motion generation
    Ran Dong
    Qiong Chang
    Soichiro Ikuno
    [J]. Neural Computing and Applications, 2023, 35 : 23343 - 23356
  • [36] Human-Robot Trust and Cooperation Through a Game Theoretic Framework
    Paeng, Erin
    Wu, Jane
    Boerkoel, James C., Jr.
    [J]. THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2016, : 4246 - 4247
  • [37] Procedural content generation based on a genetic algorithm in a serious game for obstructive sleep apnea
    Mitsis, Konstantinos
    Kalafatis, Eleftherios
    Zarkogianni, Konstantia
    Mourkousis, George
    Nikita, Konstantina S.
    [J]. 2020 IEEE CONFERENCE ON GAMES (IEEE COG 2020), 2020, : 694 - 697
  • [38] Procedural Content Generation using Artificial Intelligence for Unique Virtual Reality Game Experiences
    Assuncao Campos, Joao Pedro
    Rieder, Rafael
    [J]. 2019 21ST SYMPOSIUM ON VIRTUAL AND AUGMENTED REALITY (SVR 2019), 2019, : 147 - 151
  • [39] BiLSTM and dynamic fuzzy AHP-GA method for procedural game level generation
    Murat İnce
    [J]. Neural Computing and Applications, 2021, 33 : 9761 - 9773
  • [40] Procedural Content Generation using Neuroevolution and Novelty Search for Diverse Video Game Levels
    Beukman, Michael
    Cleghorn, Christopher W.
    James, Steven
    [J]. PROCEEDINGS OF THE 2022 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'22), 2022, : 1028 - 1037
12345