Summary of Who Speaks Next? Multi-party Ai Discussion Leveraging the Systematics Of Turn-taking in Murder Mystery Games, by Ryota Nonomura and Hiroki Mori
Who Speaks Next? Multi-party AI Discussion Leveraging the Systematics of Turn-taking in Murder Mystery Games
by Ryota Nonomura, Hiroki Mori
First submitted to arxiv on: 6 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A new framework called “Murder Mystery Agents” is proposed to improve dialogue control and autonomous decision making among artificial intelligence (AI) agents. The approach applies conversational norms such as adjacency pairs and turn-taking found in conversation analysis to AI agents’ dialogue control. To evaluate the effectiveness of this new approach, a reasoning-type table-top role-playing game called “Murder Mystery” is employed. The game requires complex social reasoning and information manipulation, which are challenging for AI agents to achieve. The proposed framework integrates next speaker selection based on adjacency pairs and a self-selection mechanism that takes agents’ internal states into account to achieve more natural and strategic dialogue. Experimental results showed that the implementation of the next speaker selection mechanism significantly reduced dialogue breakdowns and improved the ability of agents to share information and perform logical reasoning. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI researchers have developed a new way for artificial intelligence (AI) agents to talk like humans. The AI agents are programmed to follow rules from human conversation, such as taking turns speaking. This helps them work together better and avoid misunderstandings. To test this approach, scientists used a game called “Murder Mystery” where players work together to solve a puzzle. The results showed that the new way of talking reduced mistakes and helped the AI agents share information more effectively. |
