About this Research Topic
In the rapidly evolving landscape of generative artificial intelligence (AI), the interaction between human and artificial agents has become increasingly complex and multifaceted. This Research Topic aims to explore these interactions' systemic and multi-agent dimensions, focusing on the dynamics at both the user interface level and the internal communication and cooperation mechanisms between human and artificial agents.
The integration of Large Language Models (LLMs) like GPT, Large Action Models (LAMs) such as Rabbit, and Text-to-Image (TTI) platforms like DALL-E presents unique opportunities and challenges. This Research Topic invites contributions that examine these interactions through a systemic lens, investigating how diverse agents with varying capabilities, roles, and goals engage in continuous coordination and communication processes.
The primary objective of this Research Topic is to address the complex dynamics of human-artificial agent interactions in the age of generative AIs. By adopting a multi-agent approach, we aim to uncover how these interactions can be optimized to enhance overall system performance and user experience. This involves understanding the protocols and procedures that govern these interactions and identifying potential emergent behaviors that could be leveraged for improved collaboration between human and artificial agents.
The concept of Human-Computer Interaction (HCI) has evolved significantly with the advent of generative AI technologies. Traditional HCI frameworks are being redefined by introducing advanced computational agents interacting with human users and other artificial agents within a networked ecosystem. These interactions are characterized by a continuous exchange of information and coordinated efforts to achieve collective goals. This Research Topic seeks to provide a comprehensive understanding of these complex interactions.
We welcome submissions that explore various aspects of the interaction between human and artificial agents. Topics of interest include, but are not limited to:
• Theoretical frameworks and models for multi-agent HCI systems;
• Case studies on the integration of LLMs, LAMs, and TTI platforms in HCI;
• Protocols and mechanisms for agent communication and coordination;
• Emergent behaviors in multi-agent systems and their implications;
• Human-in-the-loop methodologies and their effectiveness;
• Practical applications and challenges in implementing multi-agent HCI systems.
We are interested in a range of manuscript types, including original research articles, review articles, theoretical papers, and case studies. Contributions should provide new insights into the systemic interactions between human and artificial agents and offer practical solutions or frameworks that can be applied in real-world scenarios.
The integration of Large Language Models (LLMs) like GPT, Large Action Models (LAMs) such as Rabbit, and Text-to-Image (TTI) platforms like DALL-E presents unique opportunities and challenges. This Research Topic invites contributions that examine these interactions through a systemic lens, investigating how diverse agents with varying capabilities, roles, and goals engage in continuous coordination and communication processes.
The primary objective of this Research Topic is to address the complex dynamics of human-artificial agent interactions in the age of generative AIs. By adopting a multi-agent approach, we aim to uncover how these interactions can be optimized to enhance overall system performance and user experience. This involves understanding the protocols and procedures that govern these interactions and identifying potential emergent behaviors that could be leveraged for improved collaboration between human and artificial agents.
The concept of Human-Computer Interaction (HCI) has evolved significantly with the advent of generative AI technologies. Traditional HCI frameworks are being redefined by introducing advanced computational agents interacting with human users and other artificial agents within a networked ecosystem. These interactions are characterized by a continuous exchange of information and coordinated efforts to achieve collective goals. This Research Topic seeks to provide a comprehensive understanding of these complex interactions.
We welcome submissions that explore various aspects of the interaction between human and artificial agents. Topics of interest include, but are not limited to:
• Theoretical frameworks and models for multi-agent HCI systems;
• Case studies on the integration of LLMs, LAMs, and TTI platforms in HCI;
• Protocols and mechanisms for agent communication and coordination;
• Emergent behaviors in multi-agent systems and their implications;
• Human-in-the-loop methodologies and their effectiveness;
• Practical applications and challenges in implementing multi-agent HCI systems.
We are interested in a range of manuscript types, including original research articles, review articles, theoretical papers, and case studies. Contributions should provide new insights into the systemic interactions between human and artificial agents and offer practical solutions or frameworks that can be applied in real-world scenarios.
Keywords: Human-Computer Interaction, Multi-Agent Systems, Generative AI, Large Language Models, Digital Collaboration, Human-Machine Cooperation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
