Thailand

As Large Language Models (LLMs) and multi-agent systems are increasingly employed in intricate social environments, the research on how human interact with LLMs/agents become promising. This study aims to explore the dynamics of Human-AI interaction through a case study of the Diplomacy game, a strategic board game renowned for its emphasis on negotiation and alliance formation. The research investigates how agents and human influence each other on decision-making, trust, and strategy within interactive settings, specifically focusing on whether agents can mimic human-like strategic behaviors including deception, and how this affects human player perceptions and actions. To this end, we propose to utilize LLMs to play the game with integrated natural language processing capabilities for negotiating and strategizing. The experimental design\footnote{As this extended abstract is a position paper, we haven&#39;t yet provide experimental results but some tentative design.} will involve mixed groups of human and AI players, allowing for the analysis of game dynamics across different team configurations.

ACL 2024

Exploring Human-AI Interaction: A Case Study on the Diplomacy Game

human-ai interaction

As Large Language Models (LLMs) and multi-agent systems are increasingly employed in intricate social environments, the research on how human interact with LLMs/agents become promising. This study aims to explore the dynamics of Human-AI interaction through a case study of the Diplomacy game, a strategic board game renowned for its emphasis on negotiation and alliance formation. The research investigates how agents and human influence each other on decision-making, trust, and strategy within interactive settings, specifically focusing on whether agents can mimic human-like strategic behaviors including deception, and how this affects human player perceptions and actions. To this end, we propose to utilize LLMs to play the game with integrated natural language processing capabilities for negotiating and strategizing. The experimental design\footnote{As this extended abstract is a position paper, we haven't yet provide experimental results but some tentative design.} will involve mixed groups of human and AI players, allowing for the analysis of game dynamics across different team configurations.

workshop paper

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The 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) will take place in Bangkok, Thailand from August 11th to 16th, 2024. More information will be announced soon.

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Learning from Teaching Assistants to Formulate Subgoals for Programming Tasks: Exploring the Potential for AI Teaching Assistants

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Vision-Language Models under Cultural and Inclusive Considerations

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Offline RLHF Methods Need More Accurate Supervision Signals

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Exploring Human-AI Interaction: A Case Study on the Diplomacy Game

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