AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2024

Ding, P.; Liu, J.; Sun, M.; Li, L.; Liu, H.

Enhancing Computational Processing Performance for Generative AI Large Models with Autonomous Decision-Making in Metaverse Applications Proceedings Article

In: Proc. - IEEE Int. Conf. Metaverse Comput., Netw., Appl., MetaCom, pp. 253–258, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833151599-7 (ISBN).

Abstract | Links | BibTeX | Tags: Adversarial machine learning, AGI (Artificial General Intelligence), Artificial general intelligence, Artificial general intelligences, Autonomous decision, Autonomous Decision-Making, Data assimilation, Data integration, Decisions makings, Digital Twin Technology, Emotion Recognition, Generative adversarial networks, Generative AI large model, Generative AI Large Models, Large models, Metaverse, Metaverses, Model Acceleration, Model Compression, Multi agent systems, Multi-agent systems, Multi-modal data, Multi-Modal Data Integration, Multiagent systems (MASs), Reinforcement Learning, Reinforcement learnings, Spatio-temporal data

@inproceedings{ding_enhancing_2024,

title = {Enhancing Computational Processing Performance for Generative AI Large Models with Autonomous Decision-Making in Metaverse Applications},

author = {P. Ding and J. Liu and M. Sun and L. Li and H. Liu},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211489063&doi=10.1109%2fMetaCom62920.2024.00048&partnerID=40&md5=ae085a7d90b12c9090f5bf7a274bc7ce},

doi = {10.1109/MetaCom62920.2024.00048},

isbn = {979-833151599-7 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Proc. - IEEE Int. Conf. Metaverse Comput., Netw., Appl., MetaCom},

pages = {253–258},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {We explore how to enhance the computational processing performance for generative AI large models with autonomous decision-making in metaverse applications. We first introduce the relationship between AI large models and the Metaverse. We elaborate on the application scenarios of generative AI large models in Metaverse, including real-time weather simulation, embodied intelligence of agents, dynamic environment interaction, and user emotion recognition. We then propose the method of Multi-Dimensional Optimization Generation Framework (MDOGF) to improve computational processing performance. The experiment results show great improvement in computational processing performance. © 2024 IEEE.},

keywords = {Adversarial machine learning, AGI (Artificial General Intelligence), Artificial general intelligence, Artificial general intelligences, Autonomous decision, Autonomous Decision-Making, Data assimilation, Data integration, Decisions makings, Digital Twin Technology, Emotion Recognition, Generative adversarial networks, Generative AI large model, Generative AI Large Models, Large models, Metaverse, Metaverses, Model Acceleration, Model Compression, Multi agent systems, Multi-agent systems, Multi-modal data, Multi-Modal Data Integration, Multiagent systems (MASs), Reinforcement Learning, Reinforcement learnings, Spatio-temporal data},

pubstate = {published},

tppubtype = {inproceedings}

}

Bojić, L.; Ðapić, V.

The Interplay of Social and Robotics Theories in AGI Alignment: Navigating the Digital City Through Simulation-based Multi-Agent Systems Proceedings Article

In: N., Zdravkovic; University, Belgrade Tadeusa Koscuska 63 Belgrade Metropolitan; D., Domazet; University, Tadeusa Koscuska 63 Belgrade Belgrade Metropolitan; S., Lopez-Pernas; of Eastern Finland, Yliopistokatu-2 Joensuu University; M.A., Conde; de Vegazana S/N University of Leon, Leon Campus; P., Vijayakumar (Ed.): CEUR Workshop Proc., pp. 58–63, CEUR-WS, 2024, ISBN: 16130073 (ISSN).

Abstract | Links | BibTeX | Tags: Artificial general intelligence, Artificial general intelligences, Autonomous agents, Decision making, Decision theory, Decisions makings, Human values, Intelligent Agents, Language Model, Large language model, large language models, Multi agent systems, Philosophical aspects, Robotic theory, Robotics, Robotics Theories, Simulation based approaches, Simulation platform, Simulation-Based Approach, Smart city, Social Theories, Social theory, Theoretical framework, Virtual cities, Virtual Reality

@inproceedings{bojic_interplay_2024,

title = {The Interplay of Social and Robotics Theories in AGI Alignment: Navigating the Digital City Through Simulation-based Multi-Agent Systems},

author = {L. Bojić and V. Ðapić},

editor = {Zdravkovic N. and Belgrade Tadeusa Koscuska 63 Belgrade Metropolitan University and Domazet D. and Tadeusa Koscuska 63 Belgrade Belgrade Metropolitan University and Lopez-Pernas S. and Yliopistokatu-2 Joensuu University of Eastern Finland and Conde M.A. and Leon Campus de Vegazana S/N University of Leon and Vijayakumar P.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193478708&partnerID=40&md5=6a9fd04d5bbf8b876ba508bef1c09076},

isbn = {16130073 (ISSN)},

year  = {2024},

date = {2024-01-01},

booktitle = {CEUR Workshop Proc.},

volume = {3676},

pages = {58–63},

publisher = {CEUR-WS},

abstract = {This study delves into the task of aligning Artificial General Intelligence (AGI) and Large Language Models (LLMs) to societal and ethical norms by using theoretical frameworks derived from social science and robotics. The expansive adoption of AGI technologies magnifies the importance of aligning AGI with human values and ethical boundaries. This paper presents an innovative simulation-based approach, engaging autonomous’digital citizens’ within a multi-agent system simulation in a virtual city environment. The virtual city serves as a platform to examine systematic interactions and decision-making, leveraging various theories, notably, Social Simulation Theory, Theory of Reasoned Action, Multi-Agent System Theory, and Situated Action Theory. The aim of establishing this digital landscape is to create a fluid platform that enables our AI agents to engage in interactions and enact independent decisions, thereby recreating life-like situations. The LLMs, embodying the personas in this digital city, operate as the leading agents demonstrating substantial levels of autonomy. Despite the promising advantages of this approach, limitations primarily lie in the unpredictability of real-world social structures. This work aims to promote a deeper understanding of AGI dynamics and contribute to its future development, prioritizing the integration of diverse societal perspectives in the process. © 2024 Copyright for this paper by its authors.},

keywords = {Artificial general intelligence, Artificial general intelligences, Autonomous agents, Decision making, Decision theory, Decisions makings, Human values, Intelligent Agents, Language Model, Large language model, large language models, Multi agent systems, Philosophical aspects, Robotic theory, Robotics, Robotics Theories, Simulation based approaches, Simulation platform, Simulation-Based Approach, Smart city, Social Theories, Social theory, Theoretical framework, Virtual cities, Virtual Reality},

pubstate = {published},

tppubtype = {inproceedings}

}