Exploring the Potential of Conversational AI Support for Agent-Based Social Simulation Model Design
University of Nottingham（诺丁汉大学）
Peer-Olaf Siebers
备注：
This paper has been published in the Journal of Artificial Societies and Social Simulation 28 (3) 2. Please refer to the published version at [https://doi.org/10.18564/jasss.5681]
发表信息：
Journal of Artificial Societies and Social Simulation 28(3) 2, 2025
ChatGPT, the AI-powered chatbot with a massive user base of hundreds of millions, has become a global phenomenon. However, the use of Conversational AI Systems (CAISs) like ChatGPT for research in the field of Social Simulation is still limited. Specifically, there is no evidence of its usage in Agent-Based Social Simulation (ABSS) model design. This paper takes a crucial first step toward exploring the untapped potential of this emerging technology in the context of ABSS model design. The research presented here demonstrates how CAISs can facilitate the development of innovative conceptual ABSS models in a concise timeframe and with minimal required upfront case-based knowledge. By employing advanced prompt engineering techniques and adhering to the Engineering ABSS framework, we have constructed a comprehensive prompt script that enables the design of conceptual ABSS models with or by the CAIS. A proof-of-concept application of the prompt script, used to generate the conceptual ABSS model for a case study on the impact of adaptive architecture in a museum environment, illustrates the practicality of the approach. Despite occasional inaccuracies and conversational divergence, the CAIS proved to be a valuable companion for ABSS modellers.
Exploring the Impact of Personality Traits on Conversational Recommender Systems: A Simulation with Large Language Models
Chinese University of Hong Kong（香港中文大学）；National University of Singapore（新加坡国立大学）；Singapore Management University（新加坡管理大学）；Hong Kong Baptist University（香港浸会大学）；Huazhong University of Science and Technology（华中科技大学）
To explore the limit of dialogue generation pre-training, we present the models of PLATO-XL with up to 11 billion parameters, trained on both Chinese and English social media conversations. To train such large models, we adopt the architecture of unified transformer with high computation and parameter efficiency. In addition, we carry out multi-party aware pre-training to better distinguish the characteristic information in social media conversations. With such designs, PLATO-XL successfully achieves superior performances as compared to other approaches in both Chinese and English chitchat. We…
BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Virginia Tech（弗吉尼亚理工大学）；Bangladesh University of Engineering and Technology（孟加拉工程与技术大学）；BRAC University（BRAC大学）；University of Toronto（多伦多大学）
EventChat: Implementation and user-centric evaluation of a large language model-driven conversational recommender system for exploring leisure events in an SME context
Swiss Federal Institute of Technology, Zurich（苏黎世联邦理工学院）
Playpen: An Environment for Exploring Learning Through Conversational Interaction
University of Potsdam（波恩大学）；University of Trento（特伦特大学）；Saarland University（萨尔大学）；ETH Zurich（苏黎世联邦理工学院）；Amsterdam UMC（阿姆斯特丹医疗中心）；Free University of Bozen Bolzano（博兹纳自由大学）；University of Amsterdam（阿姆斯特丹大学）；Heriot-Watt University（赫里奥特-瓦特大学）；DFKI（德意志联邦研究所）；UCL（伦敦大学学院）；University of Edinburgh（爱丁堡大学）
Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis
Department of Electrical and Computer Engineering, Seoul National University（电子与计算机工程系，首尔国立大学）；Interdisciplinary Program in Artificial Intelligence, Seoul National University（人工智能跨学科计划，首尔国立大学）；AIIS, ASRI, INMC, and ISRC, Seoul National University（人工智能研究所、人工智能研究机构、智能网络中心和智能系统研究组，首尔国立大学）
Goal-oriented conversational agents are becoming prevalent in our daily lives. For these systems to engage users and achieve their goals, they need to exhibit appropriate social behavior as well as provide informative replies that guide users through tasks. The first component of the research in this paper applies statistical modeling techniques to understand conversations between users and human agents for customer service. Analyses show that social language used by human agents is associated with greater users' responsiveness and task completion. The second component of the research is the c…
Conversational search presents opportunities to support users in their search activities to improve the effectiveness and efficiency of search while reducing their cognitive load. Limitations of the potential competency of conversational agents restrict the situations for which conversational search agents can replace human intermediaries. It is thus more interesting, initially at least, to investigate opportunities for conversational interaction to support less complex information retrieval tasks, such as typical web search, which do not require human-level intelligence in the conversational …
"I Like Sunnie More Than I Expected!": Exploring User Expectation and Perception of an Anthropomorphic LLM-based Conversational Agent for Well-Being Support
University of Toronto（多伦多大学）；Flourish Science（弗洛里什科学公司）；Northeastern University（东北大学）
We report on the design and development of the CASPR system, a socialbot designed to compete in the Amazon Alexa Socialbot Challenge 4. CASPR's distinguishing characteristic is that it will use automated commonsense reasoning to truly "understand" dialogs, allowing it to converse like a human. Three main requirements of a socialbot are that it should be able to "understand" users' utterances, possess a strategy for holding a conversation, and be able to learn new knowledge. We developed techniques such as conversational knowledge template (CKT) to approximate commonsense reasoning needed to ho…
This work aims to connect the Automotive User Interfaces (Auto-UI) and Conversational User Interfaces (CUI) communities through discussion of their shared view of the future of automotive conversational user interfaces. The workshop aims to encourage creative consideration of optimistic and pessimistic futures, encouraging attendees to explore the opportunities and barriers that lie ahead through a game. Considerations of the future will be mapped out in greater detail through the drafting of research agendas, by which attendees will get to know each other's expertise and networks of resources…
Exploring Conversational Design Choices in LLMs for Pedagogical Purposes: Socratic and Narrative Approaches for Improving Instructor's Teaching Practice
"Mango Mango, How to Let The Lettuce Dry Without A Spinner?": Exploring User Perceptions of Using An LLM-Based Conversational Assistant Toward Cooking Partner
This paper presents a mobile audio space intended for use by gelled social groups. In face-to-face interactions in such social groups, conversational floors change frequently, e.g., two participants split off to form a new conversational floor, a participant moves from one conversational floor to another, etc. To date, audio spaces have provided little support for such dynamic regroupings of participants, either requiring that the participants explicitly specify with whom they wish to talk or simply presenting all participants as though they are in a single floor. By contrast, the audio space …
The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user's input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user's intention to drive the conversation in specific dir…
An important step towards enabling English language learners to improve their conversational speaking proficiency involves automated scoring of multiple aspects of interactional competence and subsequent targeted feedback. This paper builds on previous work in this direction to investigate multiple neural architectures -- recurrent, attention and memory based -- along with feature-engineered models for the automated scoring of interactional and topic development aspects of text dialog data. We conducted experiments on a conversational database of text dialogs from human learners interacting wi…
In this paper we describe the requirements and early system design for a smart conversational agent that can assist older adults in the reminiscence process. The practice of reminiscence has well documented benefits for the mental, social and emotional well-being of older adults. However, the technology support, valuable in many different ways, is still limited in terms of need of co-located human presence, data collection capabilities, and ability to support sustained engagement, thus missing key opportunities to improve care practices, facilitate social interactions, and bring the reminiscen…
Previous studies have highlighted the benefits of pedagogical conversational agents using socially-oriented conversation with students. In this work, we examine the effects of a conversational agent's use of affiliative and self-defeating humour -- considered conducive to social well-being and enhancing interpersonal relationships -- on learners' perception of the agent and attitudes towards the task. Using a between-subjects protocol, 58 participants taught a conversational agent about rock classification using a learning-by-teaching platform, the Curiosity Notebook. While all agents were cur…
Conversational AI agents are proliferating, embodying a range of devices such as smart speakers, smart displays, robots, cars, and more. We can envision a future where a personal conversational agent could migrate across different form factors and environments to always accompany and assist its user to support a far more continuous, personalized, and collaborative experience. This opens the question of what properties of a conversational AI agent migrates across forms, and how it would impact user perception. To explore this, we developed a Migratable AI system where a user's information and/o…
From Fake Perfects to Conversational Imperfects: Exploring Image-Generative AI as a Boundary Object for Participatory Design of Public Spaces
College of Computing and Information Science, Cornell University（康奈尔大学计算与信息科学学院）；University of Southern California（南加州大学）；College of Agriculture and Life Sciences, Cornell University（康奈尔大学农业与生命科学学院）；Studio-MLA
People with visual impairment (PVI) must interact with a world they cannot see. Remote sighted assistance has emerged as a conversational/social support system. We interviewed participants who either provide or receive assistance via a conversational/social prosthetic called Aira (https://aira.io/). We identified four types of support provided: scene description, performance, social interaction, and navigation. We found that conversational style is context-dependent. Sighted assistants make intentional efforts to elicit PVI's personal knowledge and leverage it in the guidance they provide. PVI…
